As a natural ecological fragile region, the vast desert steppe in the Inner Mongolia has a developed animal husbandry, and thus posed great impacts on soil quality. In order to accurately evaluate the current situation of soil quality in the desert steppe, it is therefore imperative to adopt a suitable method to effectively assess the soil quality in the region. In this study, the minimum data set (MDS) was established with the help of principal component analysis, Norm value calculation, and correlation analysis, and four indicators, including organic matter, sand grains, soil erosion degree, and pH, were established to evaluate the soil quality of the desert steppe in the Siziwang Banner, a county in the Inner Mongolia. The results from the minimum data set (MDS) method were validated based on the total data set (TDS) method, and the validation indicated that the MDS method can be representative of the soil quality of the study area. The results indicated: 1) the soil quality index (SQI) of 0–30 cm in more than 90% of the study area falls in the range of 0.4 and 0.6 (medium level), while the better level (SQI ≥0.6) only accounted less than 10% of the study area; 2) For the MDS indexes, soil organic matter content at all depths decreased in the southern mountains, central hills, and northern plateau, which is consistent with the changing trends of SQI; 3) The sand grain was the dominant particle in the study region, which was in accordance with the intense wind erosion; 4) The negative correlation was found between the soil pH value and SQI (the high value in pH corresponded to the low value in SQI), which reflected that soil pH has a more stressful effect on the local vegetation. Overall, the MDS indexes in this study can objectively and practically reflect the soil quality in the study area, which can provide a cost effective method for SQI assessment in the desert steppe, which is important for the further grassland ecological construction and grassland management to improve the soil quality in the desert steppes.

Structural contradictions among cities, agriculture, animal husbandry, and ecosystems in agriculture/ pastoral zones have become increasingly prominent. This study analyzed land use change for a typical farming-pastoral interlacing area in the Keerqinzuoyihou Banner, China, using land use status data from 2009 to 2017. The drivers of land use changes were determined using logistic regression analysis. The Conversion of Land Use and its Effects at Small Region Extent (CLUE-S) model simulated four scenarios (i.e., natural evolution, ecological, economic, and social benefits maximization), and there were three key findings. First, land use structure mainly consisted of cropland, forest, and grassland; these accounted for nearly 90% of the total land area. There was a rapid increase in cultivated and built-up areas from 2009 to 2017. Second, the Kappa coefficient of the CLUE-S simulated results and actual land use was 0.936, indicating high model accuracy and applicability for simulating spatial land use distribution in the study area. Third, under the natural evolution scenario, forest, grassland, water bodies, sandy land, and unused land decreased from 2017 to 2025, whereas cropland and built-up land increased. This provides a reference to guide government land use planning and measures to improve land use efficiency and optimize the industrial structure.

Soil wind erosion is one of the critical drivers of land degradation in the black soil region of northeastern China. In this study, 137Cs background value and soil wind erosion rate was studied by using 137Cs nuclide tracing technique in the black soil region of northeastern China, and wind erosion characteristics such as background value and soil erosion rate over the years were clarified, which has guiding significance for soil and water conservation and agricultural sustainable development in the black soil region of northeast China. The mean area activity of the Hilltop area was 1541 Bq·m-2, which was lower than the background value of 1879.7 Bq·m-2 in the study area. At the top of the hill, soil erosion occurred to some extent. The 137Cs profile has distributional characteristics that can be divided into three categories. Most of the 137Cs area activity in Hilltop area is evenly distributed in 0-15 cm, and the 137Cs area activity below 15 cm decreased gradually until it disappeared. The spatial difference of wind erosion rate is significant in the study area, mainly between 7.17-10.13 t·hm-2a-1. The average wind erosion rate of hilltops with different tillage quality depths has little difference. The average wind erosion rate is 8.60 t·hm-2a-1, which belongs to mild erosion. However, its erosion rate is higher than the tolerable soil loss of 2 t·hm-2a-1 in the black soil region of northeast China. As a result, soil erosion control in the black soil region of northeast China still requires attention.

Taking Baotou city as an example, we calculate carbon emissions and carbon sinks in the “Production-living-ecological space” from 2005 to 2021, and use the STIRPAT model and GM(1,1) model to analyse and forecast the factors influencing carbon emissions and carbon emissions in the next ten years. The results show that (1) the carbon emission reduction strategies for the production, living and ecological spaces of Baotou City were implemented from 2005 to 2011. The results show that: (1) from 2005 to 2021, the total carbon emissions in Baotou City increased by 103,643,100t, with a 3.2-fold increase in total carbon emissions and an average annual growth rate of 7.92%. Production space has the highest contribution to the total carbon emission, and the amount of carbon sink in ecological space is small compared to the total carbon emission. (2) According to the results of the STIRPAT model, the total population, GDP per capita, energy intensity, urbanization rate, the proportion of secondary industry and total carbon emissions in Baotou are synergistic, while the proportion of tertiary industry and total carbon emissions are antagonistic. (3) According to the prediction results of the GM(1,1) model, the total carbon emissions in Baotou will increase from 145,102,300 t to 207,230,500 t in the period of 2022-2031, which shows that the overall carbon emissions in Baotou are still on a growing trend, but the trend is gradually slowing down. Finally, on the basis of the previous study, carbon emission reduction suggestions such as optimising industrial structure and improving the efficiency of agricultural production inputs are put forward.

Cultivated land intensive utilization (CLIU) exhibits spatial heterogeneity that is influenced by both natural and anthropogenic factors, with land dissected into different scale systems; however, CLIU has not yet been systematically explored. This study takes the Beibu Gulf urban agglomeration, a national-level model area for integrated land and sea development in China, as an example to investigate the spatial heterogeneity of CLIU and explore its driving factors through multiple econometrical and geographical methods, including identifying its underlying mechanisms. The results indicate that (1) the CLIU index is 0.334, its Gini coefficient is 0.183, and its comprehensive level has a low intensity and obvious spatial nonequilibrium characteristics. Hypervariable density (50.33%) and the intraprovincial gap (45.6%) are the main sources. (2) Among the independent effects of single factors, the multiple cropping index (0.57), labor force index (0.489), and intensification of construction land (0.375) exert the most influence on CLIU spatial variation. The interaction effects of two factors primarily manifested as nonlinear enhancements, with the interaction between the labor force index and multiple cropping index being particularly noteworthy (0.859). (3) The geographically weighted regression coefficients reveal that temperature (0.332), multiple cropping index (0.211), and labor force index (0.209) have relatively large and positive impacts on CLIU, while slope (−0.1), precipitation (−0.087), and population urbanization (−0.039) have relatively small and negative impacts; all factors exhibit spatial nonstationarity. The spatial heterogeneity of CLIU in the Beibu Gulf urban agglomeration is characterized by patterns’ nonequilibrium and factors’ nonstationarity. The driving mode of multiple factors on CLIU is manifested as follows: natural factors of cropland utilization provide basic guarantees, internal factors of CLIU provide positive enhancement, and external factors of land intensive utilization provide auxiliary promotion.

In China, the New Quality Productive Forces (NQPF) and ecological restoration have become a national strategy. Investigating the interrelated mechanisms between NQPF and Territorial Spatial Ecological Restoration (TSERS) is essential for promoting high-quality development. We analyse the non-linear relationship between NQPF and TSERS employing fixed effects, moderating effects, and threshold models. The following results were observed: 1) The differences in NQPF among provinces gradually decreased and exhibited significant spatial agglomeration, while the differences in TSERS gradually increased and showed no significant spatial agglomeration; 2)The NQPF and TSERS of provincial units in China exhibited a centripetal clustering trend in the northeast-southwest direction; 3) China’s NQPF exhibited a significant and positive promotional effect on TSERS, with the regression coefficient of the main effect at 0.435 (including time-lagged effects); 4) There was a double threshold for the influence of NQPF on TSERS, with land green use efficiency being the threshold variable (the threshold values were 0.246 and 1.414, respectively); moreover, the influence of NQPF on TSERS gradually decreased after crossing the threshold value. We provide a novel perspective on examining the relationship between NQPF and ecological restoration while simultaneously evaluating the regulatory effectiveness of land green use efficiency in improving the broader scope of territorial ecological restoration. The findings suggest that the advancement of NQPF can significantly enhance TSERS. Policy recommendations include regulating the expansion of construction land, establishing criteria for ecological management, and implementing taxes on ecological restoration.