Temporal and spatial relationships between soil erosion and ecological restoration in semi-arid regions: a case study in northern Shaanxi, China

To assess the effects of the Grain for Green Program (GGP) on soil erosion is essential to support better land management policies in the Chinese Loess Plateau. Studies on the evaluation of the effects of the GGP on soil erosion have garnered heightened attention. However, few studies examined the efficiency of GGP on soil erosion control through spatial relationship analysis. Thus, this study focuses on analyzing the spatial variation relationship between soil erosion and GGP in northern Shaanxi, Chinese Loess Plateau, from 1988 to 2015. The Universal Soil Loss Equation was used to quantify changes in soil erosion at the regional and watershed scales, and the Geographically Weighted Regression model was used to analyze the spatial relationships between land use and land cover (LULC) and soil erosion. Our results indicated that the major characteristic of LULC change during the GGP was a rapid increase of vegetation area and a rapid decrease of cropland. Bare lands contributed to the most serious soil loss, followed by croplands and sparse grasslands. The GGP had a globally positive influence on the decrease in soil erosion over the study area, but the amount of soil erosion in western and northern regions maintained a severe level. Spatial heterogeneity in the nature of the relationships among different vegetation, croplands, and soil erosion was also observed. The change rate of wood and the change rate of soil erosion in northern sub-watershed represented a negative relationship, while the change rate of sparse grassland was negatively correlated to the change rate of soil erosion in 21 sub-watersheds, account for 72% of the study area. The GGP implemented in northern sub-watersheds were more effective for soil erosion control than southern sub-watersheds. We propose that current areas of vegetation can support soil erosion control in the whole northern Shaanxi, but local-scale ecological restoration can be considered in northern sub-watersheds.</p

Estimation results of the SDM model.

In regard to the comprehensive promotion of rural revitalization, the construction of digital villages is a crucial development. Because the construction of digital villages is considerably novel, the existing studies mainly focus on the theoretical aspects pertaining to the rational and practical robustness of digital villages, and with regard to regional unevenness, the number of studies that consider the current characteristics, absolute gaps, and impact mechanisms pertaining to the construction of digital villages is insufficient. Based on the regional unevenness that characterizes digital village construction, this study proposes a research framework for digital technology-enabled village construction, which integrates three major factors, namely technology, institutions, and human resources; thus, the comprehensive assessment pertaining to the level of digital village construction is enhanced. This study, which applies the aforementioned research framework, constructs an index system for evaluating the construction level of digital villages, and to reveal the characteristics pertaining to regional heterogeneity and the main influencing factors pertaining to the construction level of digital villages in China (study period; 2015–2020), it utilizes the Dagum Gini coefficient method and the spatial econometric model. Consequently, the researchers observe the following: First, the level of digital village construction in China exhibits a “W-shaped” recovery growth. Second, with respect to the regional level, the eastern region exhibits the highest level of digital village construction, followed by central and western regions; furthermore, we observe that the eastern and western regions account for the greatest intra-regional variation, and that with regard to the overall difference, the inter-regional gap represents the main causative factor. Finally, with regard to influencing factors, technology and innovation capabilities, occupational differentiation of farmers, economic development significantly contribute to the level of digital village construction, whereas fiscal autonomy exerts a significant inhibiting effect. In regard to the level of digital village construction, the research framework and results may provide a novel analytical framework for examining the main sources of regional unevenness, and it may also provide a reference for decision-making, which can influence the construction of digital villages in China as well as in other countries.</div

Dagum Gini coefficient and decomposition of digital village construction levels in China (2015–2020).

Dagum Gini coefficient and decomposition of digital village construction levels in China (2015–2020).</p

Digital rural development trends in three major regions (2015–2020).

Digital rural development trends in three major regions (2015–2020).</p

Robustness test for the impact of aging and the digital economy on total factor productivity.

Robustness test for the impact of aging and the digital economy on total factor productivity.</p

Comparison of four types of panel regression models.

Comparison of four types of panel regression models.</p

The logic of digital technology-enabled rural construction.

The logic of digital technology-enabled rural construction.</p

Robustness regression results.

In regard to the comprehensive promotion of rural revitalization, the construction of digital villages is a crucial development. Because the construction of digital villages is considerably novel, the existing studies mainly focus on the theoretical aspects pertaining to the rational and practical robustness of digital villages, and with regard to regional unevenness, the number of studies that consider the current characteristics, absolute gaps, and impact mechanisms pertaining to the construction of digital villages is insufficient. Based on the regional unevenness that characterizes digital village construction, this study proposes a research framework for digital technology-enabled village construction, which integrates three major factors, namely technology, institutions, and human resources; thus, the comprehensive assessment pertaining to the level of digital village construction is enhanced. This study, which applies the aforementioned research framework, constructs an index system for evaluating the construction level of digital villages, and to reveal the characteristics pertaining to regional heterogeneity and the main influencing factors pertaining to the construction level of digital villages in China (study period; 2015–2020), it utilizes the Dagum Gini coefficient method and the spatial econometric model. Consequently, the researchers observe the following: First, the level of digital village construction in China exhibits a “W-shaped” recovery growth. Second, with respect to the regional level, the eastern region exhibits the highest level of digital village construction, followed by central and western regions; furthermore, we observe that the eastern and western regions account for the greatest intra-regional variation, and that with regard to the overall difference, the inter-regional gap represents the main causative factor. Finally, with regard to influencing factors, technology and innovation capabilities, occupational differentiation of farmers, economic development significantly contribute to the level of digital village construction, whereas fiscal autonomy exerts a significant inhibiting effect. In regard to the level of digital village construction, the research framework and results may provide a novel analytical framework for examining the main sources of regional unevenness, and it may also provide a reference for decision-making, which can influence the construction of digital villages in China as well as in other countries.</div

The administrative units in China.

In regard to the comprehensive promotion of rural revitalization, the construction of digital villages is a crucial development. Because the construction of digital villages is considerably novel, the existing studies mainly focus on the theoretical aspects pertaining to the rational and practical robustness of digital villages, and with regard to regional unevenness, the number of studies that consider the current characteristics, absolute gaps, and impact mechanisms pertaining to the construction of digital villages is insufficient. Based on the regional unevenness that characterizes digital village construction, this study proposes a research framework for digital technology-enabled village construction, which integrates three major factors, namely technology, institutions, and human resources; thus, the comprehensive assessment pertaining to the level of digital village construction is enhanced. This study, which applies the aforementioned research framework, constructs an index system for evaluating the construction level of digital villages, and to reveal the characteristics pertaining to regional heterogeneity and the main influencing factors pertaining to the construction level of digital villages in China (study period; 2015–2020), it utilizes the Dagum Gini coefficient method and the spatial econometric model. Consequently, the researchers observe the following: First, the level of digital village construction in China exhibits a “W-shaped” recovery growth. Second, with respect to the regional level, the eastern region exhibits the highest level of digital village construction, followed by central and western regions; furthermore, we observe that the eastern and western regions account for the greatest intra-regional variation, and that with regard to the overall difference, the inter-regional gap represents the main causative factor. Finally, with regard to influencing factors, technology and innovation capabilities, occupational differentiation of farmers, economic development significantly contribute to the level of digital village construction, whereas fiscal autonomy exerts a significant inhibiting effect. In regard to the level of digital village construction, the research framework and results may provide a novel analytical framework for examining the main sources of regional unevenness, and it may also provide a reference for decision-making, which can influence the construction of digital villages in China as well as in other countries.</div

Details of digital villages: Components and variables.

Details of digital villages: Components and variables.</p