Wind erosion poses a major threat to ecosystem stability and land productivity in arid and semi-arid regions. Accurate identification of its spatiotemporal dynamics and underlying driving mechanisms is a critical prerequisite for effective risk forecasting and targeted erosion control. This study applied the Revised Wind Erosion Equation (RWEQ) model to assess the spatial distribution, interannual variation, and seasonal dynamics of the Soil Wind Erosion Modulus (SWEM) across Inner Mongolia from 1990 to 2022. The GeoDetector model was further employed to quantify dominant drivers, key interactions, and high-risk zones via factor, interaction, and risk detection. The results showed that the average SWEM across the study period was 35.65 t·ha⁻¹·yr⁻¹ and showed a decreasing trend over time. However, localised increases were observed in the Horqin and Hulun Buir sandy lands and central grasslands. Wind erosion was most intense in spring (17.64 t·ha⁻¹·yr⁻¹) and weakest in summer (5.57 t·ha⁻¹·yr⁻¹). Gale days, NDVI, precipitation, and wind speed were identified as dominant drivers. Interaction detection revealed non-linear synergies between gale days and temperature (q = 0.40) and wind speed and temperature (q = 0.36), alongside a two-factor interaction between NDVI and precipitation (q = 0.19). Risk detection indicated that areas with gale days > 58, wind speed > 3.01 m/s, NDVI < 0.2, precipitation of 30.17–135.59 mm, and temperatures of 3.01–4.23 °C are highly erosion-prone. Management should prioritise these sensitive and intensifying areas by implementing site-specific strategies to enhance ecosystem resilience.

Identifying and ranking the key drivers of grassland conversion at the county level is crucial for developing targeted policies and improving protection efficiency. However, this process faces methodological challenges because of spatial and temporal variability. Partial order theory offers a robust framework for addressing these complexities. This study applies partial order theory (POT) combined with the Hasse diagram technique (HDT) to analyze grassland conversion in the Hohhot–Baotou–Ordos region during two time periods (2000–2010 and 2010–2020). First, patterns of grassland transformation are quantified, and the dominant driving factors of grassland conversion out (GCO) are identified and ranked, highlighting regional differences and temporal shifts. By integrating POT and HDT, this study offers a novel approach to handling complex, nonlinear, and hierarchical relationships among multiple drivers. The results provide scientific insight and policy recommendations for region-specific grassland management and sustainable land-use planning. The results show that (1) transitions between grasslands and other land-use types became more frequent across the two periods. Specifically, the rates of grassland conversion out and conversion increased from 2.1% and 3.5% during the period 2000–2010 to 4.7% and 4.8% during the period 2010–2020, respectively. (2) Urbanization was the primary driver of grassland conversion in 11 and 10 of the 18 counties during the first and second periods, respectively, followed by factors related to weather variables. (3) In the future, the eastern region of the study area needs to prioritize mitigating the impacts of urban development, while the western region should focus on enhancing ecological construction projects. This study recommends adopting region-specific ecological protection and economic strategies for balanced outcomes in conservation and development.

Wind erosion is a multidimensional, dynamic process driven by natural and anthropogenic factors, but existing statistical methods struggle to capture its complex nonlinear relationships, resulting in incomplete quantification of drivers and their spatial variability. To address this, we integrate the Revised Wind Erosion Equation (RWEQ)model with explainable artificial intelligence to disentangle the spatiotemporal positive and negative effects of dominant drivers and their synergistic interactions in Inner Mongolia. Results show that, from 2000–2022, wind erosion has been decreasing on average by 1.1 t·ha⁻¹·yr⁻¹, mainly in the western deserts and locally in Hulunbuir sandy land. Severe erosion is mostly due to nature (78.7%) rather than anthropogenic (21.3%). Normalized difference vegetation index (NDVI), clay content (CL), windy days (WD), precipitation (PRE), temperature (TEM), and sand content (SA) were found to be the most important drivers of wind erosion. Critical threshold conditions for severe wind erosion are NDVI < 0.14, CL < 12%, GD > 26, PRE < 73.15 mm, and SA > 66%. When there is a certain combination of variables, wind erosion risk is greatly increased, which mainly happens in the western part of Alxa, Bayannur, and the area near the desert edge. Wind erosion control should shift toward region-specific precision management, including engineering protection, optimized grazing management, and vegetation restoration.

Grassland degradation (GD) varies markedly across space. Identifying potential drivers at the county level enables precise grassland conservation and supports a win–win between economic development and ecological protection. However, most existing studies adopt a single, region-wide lens and lack county-level analyses. Focusing on Ordos, we conduct a county-level assessment and rank potential driver groups using partial-order theory. The results indicated the following: (1) from 2000 to 2020, a total of 6.9% (6026 km²) of grassland was restored, while approximately 5.0% (4372 km²) underwent degradation, with grassland recovery outpacing degradation; (2) urbanisation and economic development were identified as the leading drivers in five counties, followed by human activities and climate (three), and livelihood development (one); and (3) Ordos should adopt county-level differentiated management strategies: controlling urban and industrial expansion in urbanisation and economic-development-dominated counties, regulating grazing and land-use activities in human-activity-dominated counties, implementing dynamic grazing bans and drought preparedness in climate-dominated counties, promoting livelihood diversification in livelihood-development-dominated counties, and applying priority-based integrated governance in multi-driver counties.

Against the backdrop of global warming, grassland degradation (GD) in arid and semi-arid regions has become a critical issue constraining ecosystem stability and socio-ecological resilience. This study aims to reveal the spatial differentiation of drivers of GD across four functional zones in Inner Mongolia—resource-oriented (RO), center-service-oriented (CSO), agro-pastoral-oriented (APO), and ecological-oriented (EO)—at the county level, using grassland conversion processes as a structural proxy. The results show that land cover changed in 19.29%, 18.69%, 17.28%, and 4.67% of the RO, CSO, APO, and EO regions, respectively, with GR mainly occurring in the RO region, while GD was more prevalent in the other zones. Drivers of GD exhibit significant variations across functional zones. In the RO zone, land use change is primarily associated with human disturbance. In the CSO and APO zones, it is associated with human activities, climatic factors, and urbanization. In the EO zone, the identified drivers show strong spatial heterogeneity, with urbanization, grazing intensity, and climate change emerging as key associated factors in the Hulunbuir, Xilingol, and Arxar regions. Overall, the results reveal a spatial gradient in the relative importance of anthropogenic pressure and climatic stress, with broader implications for adaptive and place-specific dryland governance under ongoing warming and increasing aridification.