In recent years, the biogeochemical behavior and environmental impact of Selenium (Se) on soil-plant systems have received widespread attention, and traditional statistical methods reveal generally positive correlations between rice Se and soil Se. However, that initial positive relationship may have been obscured by local external factors. Using local scale data from the geochemical evaluation of land quality project, this work employed geographically weighted regression (GWR) to examine the spatial variation of rice Se (as the dependent variable) and soil Se (as the independent variable) in Guangxi. Strong and weak correlation coefficients occur between rice Se and soil Se, thereby indicating that their relationships are spatially varying. Guangxi is characterized by significantly positive correlations in most areas, with weak correlations mostly found in the south-western and central-eastern regions. Areas with weak correlation can be divided into two patterns: high soil Se with low rice Se and high rice Se with low soil Se. The unique patterns are correlated with distinct natural factors, particularly the abundance of Fe-rich soils in the carbonate area; by contrast, sandstone areas in central Guangxi may have been affected by anthropogenic activities. To reveal the spatially varying relationships at the local scale, we employed GWR, an effective tool that allowed us to identify the association between environmental variables and influencing factors and explore spatially varying relationships between them. This study breaks through the existing understanding that soil Se is completely positively correlated with rice Se for the first time, and concludes that their correlation is spatially variable, providing an effective approach for the study of complex relationships.
Keywords: Geographically weighted regression; Guangxi; Selenium; Soil-rice system.
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