With the rapid advancement of urbanization and industrialization, the contradiction between the social economy and resources and the environment has become increasingly prominent. On the basis of limited land resources, the way to promote multi-objective comprehensive development such as economic, social development and ecological and environmental protection through structure and layout regulation, so as to maximize regional comprehensive benefits, is an important task of current land spatial planning. Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Based on land suitability evaluation, we predict and optimize the land use structure of the study area in 2030 and evaluate and compare ecosystem services. Based on remote-sensing images and eco-environmental data from 1985 to 2014 in the study area, land use/land cover change (LUCC) and future simulation data were obtained by using supervised classification, landscape metrics and the CA-Markov model. The ecosystem services were evaluated by the InVEST model. The analytic hierarchy process (AHP) method was used to evaluate the land suitability for LUCC. Finally, the LUCC in 2030 under two different scenarios, Scenario_1 (prediction) and Scenario_2 (optimization), were evaluated, and the ecosystem service functions were compared. In the last 30 years, the landscape in the study area has gradually fragmented, and the built-up land has expanded rapidly, increased by one-third, mainly at the cost of cropland, orchards and wasteland. According to the suitability evaluation, giving priority to the land use types with higher environmental requirements will ensure the study area has a higher ecosystem service value. The rapid development of urbanization has a far-reaching impact on regional LUCC. Intensive land resources need reasonable and scientific land use planning, and land use planning should be based on the suitability evaluation of land resources, which can improve the regional ecosystem service function.

Background: Vegetation roots are considered to play an effective role in controlling soil erosion by benefiting soil hydrology and mechanical properties. However, the correlation between soil hydrology and the mechanical features associated with the variation root system under different vegetation types remains poorly understood. Methods: We conducted dye-tracer infiltration to classify water flow behavior and indoor experiments (including tests on soil bulk density, soil organic carbon, mean weight diameter, soil cohesion, root density, etc.) to interpret variation patterns in three forest systems (coniferous and broad-leaved mixed forest, CBF; coniferous forest, CF; Phyllostachys edulis, PF) and fallow land (FL). Results: Based on the soil dye-tracer infiltration results, the largest dyeing area was observed in CF (36.96%), but CF also had the lowest infiltration rate (60.3 mm·min⁻¹). The soil under CBF had the highest shear strength, approximately 25% higher than other vegetation types. CF exhibited the highest aggregate stability, surpassing CBF by 98.55%, PF by 34.31%, and FL by 407.41%, respectively. Additionally, PF forests showed the greatest root biomass and length. The results of correlation analysis and PCA reveal complex relationships among hydrological and mechanical soil traits. Specifically, soil cohesion does not exhibit significant correlations with hydrological traits such as the dyeing area, while traits like MWD and PAD show either positive or negative associations with hydrological traits. Root traits generally exhibit positive relationships with soil mechanical traits, with limited significant correlations observed with hydrological traits. Conversely, we found that root biomass contributes significantly to the dyeing area (accounting for 51.48%). Conclusions: Our findings indicate that the reforestation system is a successful approach for conserving water and reducing erosion by increasing soil-aggregated stability and shear strength, causing water redistribution to be more homogenized across the whole soil profile.

The Karst plateau region has a unique natural erosion environment and sharp human–land conflicts. This study selected Bijie City, Northwest Guizhou, as the study area. To quantitatively analyze the human and natural impacts on soil erosion in this area, this paper evaluated the anthropogenic and natural soil erosion based on the Revised Universal Soil Loss Equation (RUSLE) coupled with the Quantitative Analytical Model (QAM). The results showed the following: (1) the total soil erosion modulus in the study area showed an increasing trend: 37.86 t/(ha·a) in 2010, 42.12 t/(ha·a) in 2015, and 48.67 t/(ha·a) in 2020; (2) human activities reduced soil erosion, with an anthropogenic soil erosion modulus of −13.79 t/(ha·a) in 2015 and −17.36 t/(ha·a) in 2020, indicating that human activities, such as projects of returning farmland to forests and rocky desertification control, played a key role in decreasing soil erosion in the study area.; and (3) the percentage of the area of soil erosion deterioration dominated by natural factors (AGN) is gradually decreasing, 89.47% in 2015 and 81.85% in 2020; the percentage of the area of soil erosion deterioration dominated by human activities (AGH) is increasing from 6.17% in 2015 to 13.80% in 2020; and the percentage of the area of soil erosion mitigation caused by human activities (ALH) and the area of soil erosion not affected by natural and human activities (NNH) showed no significant change. This result suggests more attention should be paid to the area of AGH to control soil erosion. This study analyzed the roles of natural factors as well as human activities in the Karst plateau, enriched the application scope of the QAM, and provided new ideas for theoretical research in this field.

The mechanism of soil detachment on steep slopes is obviously different from that on gentle slopes. However, the slope effect of soil detachment remains unclear. The objective of this study was to quantify the slope effect of soil detachment capacity at the varying hydrodynamic characteristics. In this study, the soil detachment capacity (Dc) on clay loam and hydrodynamic characteristics were measured by conducting the runoff scouring experiments at 10 slope gradients (1.7–57.7%) and 5 unit flow discharges (0.022–0.089 m²·min⁻¹). The results showed that the relationships between Dc and hydrodynamic parameters were affected by slope gradient. Based on the optimal functional relationship, the hydrodynamic characteristics (flow velocity, flow shear stress, stream power, unit stream power, and unit energy) calculated by maximum and minimum Dc in this study changed by 19.91–95138.10%, and the Dc calculated by the maximum and minimum hydrodynamic characteristics could differ by up to nine orders of magnitude. Overall, the power function of hydrodynamic parameters was superior to the linear function in different slope gradients. The stream power was the best predictor for Dc compared with other hydrodynamic parameters. For all combinations of slope gradients, the adjusted coefficient of determination (Adj. R²) of the power relationship between Dc and stream power was 9.41–27.40% higher than it was between Dc and other hydrodynamic parameters. The coefficient and index of power function for different hydrodynamic parameters showed a trend change with increasing slope gradient, indicating that there was a slope effect on Dc. Further analysis found that Dc could be well predicted using a power combination equation of slope gradient, flow velocity, and flow depth (Adj. R² = 0.96). This study helps to better understand the mechanism of soil detachment and emphasizes that the slope effect should be considered when establishing a soil detachment equation.