APPLICATION OF LANDSCAPE PATTERN ANALYSIS TO QUANTITATIVELY EVALUATE THE SPATIAL STRUCTURE CHARACTERISTICS OF PREFERENTIAL FLOW PATHS IN FARMLAND

The distribution of soil preferential paths is a natural process with highly spatiotemporal variability. However, an adequate analysis method to evaluate the spatial structures of soil preferential paths from the viewpoint of ecology has not yet been developed. Hence, the quantification of the complicated distribution patterns of soil preferential paths and their relation to biota activities from the ecological perspective remains elusive. This article presents a new method that combines the image processing technology of morphology and spatial pattern analysis (i.e., quantitative parameters W-i, M-i, U-i, and g(r) function) of landscape ecology to quickly observe and quantify the spatial distribution characteristics of preferential flow paths. The study was conducted on soybean fields in the Three Gorges Reservoir Areas in China. Results demonstrated that the proposed method can describe the spatial connectivity, development degree, and rapid water conductivity of different preferential flow paths (paths of 2.5-5.0 mm were the highest, whereas paths of 1.0-2.5 mm were the lowest). All the preferential flow paths, except for the paths of 1.0-2.5 mm (random distribution pattern), mainly demonstrated a gradual tendency to follow a clumped distribution pattern and community structure relative to soil depth. In addition, all the paths showed low spatial complexity because of their uniform composition relative to soil depth. Soil intra-structure (<1.0 mm, 1.0-2.5 mm, 2.5-5.0 mm, and >5.0 mm) and plant roots effectively influenced the distribution patterns and formation of the preferential paths in the deep farmland soil. Plant roots, in particular, significantly influenced the formation and distribution of the preferential flow paths of 1.0-2.5 mm in the soybean field. Compared with existing methods (e.g., dye tracing, resin impregnation, water breakthrough curve analysis, and computed tomography technique), the proposed method can provide more significant spatial structure information from an ecological perspective. Such information can help expand our understanding of the spatial structures of preferential flow paths and the underlying ecological formation processes in soil ecosystems. The method is also effective, convenient, rapid, and economical when used to the study the spatial structures of soil preferential paths at different field scales for soil management.