Multiscale spatiotemporal characteristics of landscape patterns, hotspots, and influencing factors for soil erosion

Soil erosion is an increasingly serious eco-environmental problem, and effective control of soil erosion is an important part of soil resource protection and ecological restoration. In this study, the multi-scale characteristics and influencing factors of soil erosion were analyzed in the Beijing–Tianjin–Hebei (BTH) region from 2000 to 2015. The results showed that the average soil erosion in the study area was 3500 t/(km2·a), in which the severe erosion areas accounted for 10% of the total area. Although the total soil erosion rate decreased by 60% from 2000 to 2015, the rate of current soil erosion was higher than the soil loss tolerance. The severe erosion area had the highest aggregation index, making it the most suitable for centralized treatment. Meanwhile, the fractal dimension index of severe erosion showed a downward trend from 2000 to 2015. This decrease in complexity led to a more optimistic conservation situation. The hotspot areas overlapped with the relatively high erosion zones and were aggregated as three large patches in the northern, southwestern, and southern BTH regions. Soil erosion distribution depends on both anthropogenic activities and natural conditions. The slope factor, which reflects the impact of natural factors on soil erosion, was the most dominant factor on soil erosion from 2000 to 2010. Conversely, the land use factor, which is mainly controlled by humans, became the dominant factor in 2015. The distribution characteristics and influencing factors of soil erosion both had scale effects. As the scale decreased from city to town, the patches of high and severe erosion classes became more regular and aggregated, the hotspot area had the most concentrated and severe soil erosion rate at the town scale, and human impacts became dominant. Conservation targeting hotspot areas measured at the town scale, which was 20% of the total area, could reduce the total soil loss by 38%. For a region with a complex structure, the main influencing factors showed strong spatial dependence.