An analysis of land use/cover change (LUCC) on the Loess Plateau over the past 30 years and its environmental effects was performed to provide scientific guidance for a sustainable development policy for the regional ecological environment and social economy. Geostatistical and trend analyses are used to study the LUCC characteristics, driving forces and environmental effects, and the relationship between LUCC and regional sustainable development is explored. The following results were obtained: (1) Overall, the land use structure has not changed, with grassland, farmland, and forest land remaining dominant; however, the vegetation coverage has significantly increased, especially in the central area. (2) LUCC is affected by climate change and human activities, with greater climate change impacts in the northwest than the southeast and greater among which human-induced impacts on the hilly/gully region in the central part. (3) LUCC will produce long-term ecological and environmental processes, such as surface runoff, soil erosion, soil moisture and carbon cycling. Vegetation restoration has both negative and positive effects on the regional ecological environment. Vegetation productivity on the Loess Plateau has approached the water resource carrying capacity threshold. Therefore, improving artificial vegetation stability and promoting the water resources balance have become the main strategies for promoting sustainable development on the Loess Plateau.

In arid and semi-arid areas, interspecific below-ground competition is prominent in agroforestry systems. To provide theoretical and technical guidance for the scientific management of apple–crop intercropping systems, a field study was conducted in the Loess Plateau of China to examine the variation of fine roots distribution in apple–crop intercropping systems. The fine roots of apple trees and crops (soybean (Glycine max (L.) Merr) or peanuts (Arachis hypogaea Linn.)) were sampled to 100 cm depth at ten distances from the tree row using the stratified excavation method. The results showed that the vertical distribution of fine roots between intercropped apple trees and intercropped crops were skewed and overlapped. Apple–crop intercropping inhibited the fine roots of apple trees in the 0–60 cm soil depth, but promoted their growth in the 60–100 cm soil depth. However, apple–crop intercropping inhibited the fine roots of intercropped crops in the 0–100 cm soil depth. For the fine roots of each component of the apple–crop intercropping systems, variation in the vertical distribution was much greater than variation in the horizontal distribution. Compared with monocropped systems, apple–crop intercropping caused the fine roots of intercropped apple trees to move to deeper soil, and those of intercropped crops to move to shallower soil. Additionally, apple–crop intercropping slightly inhibited the horizontal extension of the fine-root horizontal barycentre (FRHB) of intercropped apple trees and caused the FRHB of intercropped crops to be slightly biased towards the north of the apple tree row. Variation of the fine roots distribution of each component of the apple–soybean intercropping system was greater than that of the apple–peanut intercropping system. Thus, the interspecific below-ground competition of the apple–peanut intercropping system was weaker than that of the apple–soybean intercropping system. Intense competition occurred in the apple–peanut intercropping system and the apple–soybean intercropping system was in sections whose distance ranged from 0.5–1.3 and 0.5–1.7 m from the tree row, respectively. The interspecific below-ground competition was fiercer on the south side of the apple tree row than on the north side.

To provide a scientific basis and technical support for agroforestry management practices, such as interrow configuration and soil water and fertilizer management, a stratified excavation method was performed both to explore the fine-root spatial distribution and niche differentiation and to quantify the below-ground interspecific competition status of 3-, 5-, and 7-year-old apple (Malus pumila M.)–soybean (Glycine max L. Merr.) intercropping systems and monocropping systems. The fine roots of older trees occupied a larger soil space and had both a greater fine-root biomass density (FRMD) and a greater ability to reduce the FRMD of soybean, but this ability decreased with the distance from the apple tree row. Similarly, the FRMD of apple trees was also adversely affected by soybean plants, but this effect gradually increased with a decrease in tree age or with the distance from the tree row. Compared with that of the 3- and 5-year-old monocropped apple trees, the FRMD of the 3- and 5-year-old intercropped apple trees increased in the 40–100 cm and 60–100 cm soil layers, respectively. However, compared with that of the 7-year-old apple and soybean monocropping systems, the FRMD of the 7-year-old intercropped apple trees and soybean plants decreased in each soil layer. Compared with that of the corresponding monocropped systems, the fine-root vertical barycenter (FRVB) of the intercropped apple trees displaced deeper soil and that of the intercropped soybean plants displaced shallower soil. Furthermore, the FRVB of both intercropped apple trees and intercropped soybean plants displaced shallower soil with increasing tree age. Intense below-ground interspecific competition in the 3-, 5-, and 7-year-old apple–soybean intercropping systems occurred in the 0–40 cm soil layer at distances of 0.5–0.9, 0.5–1.3, and 0.5–1.7 m from the apple tree row, respectively.

The canopy shading model is widely used in agroforestry systems. However, the canopy shading model cannot be verified by the measured shading distribution of an apple tree due to the uneven ground and adjacent apple trees. This paper measures the spatial‒temporal distribution of the shading of apple trees based on the similarity principle of parallel solar light combined with 3D printing technology to improve the canopy shading model. The following results are drawn: (1) The current widely used canopy shading model does not consider the effect of the canopy penumbra, resulting in poor simulation accuracy in the shading distribution compared to the actual measurement; (2) The effect of canopy penumbra causes the deflection of sunlight. Hence, the paper presents the deflection equation of sunlight with statistically defined parameters derived using measured data of the shading distribution. The deflection equation of sunlight is added to the improved canopy shading model. The improved model can accurately simulate the shading distribution of an apple tree, and the simulation accuracy exceeds 94.12% when compared with the shading distribution of an apple tree; (3) The improved canopy shading model is applied to simulate the spatial‒temporal distribution of the shading of apple trees in a conventional arrangement (4 m × 5 m), and the simulation accuracy exceeds 89%. Thus, the improved canopy shading model can be applied to simulate the spatial‒temporal distribution of shading of apple trees.