Publications by authors named "Jiu-Fen Liu"
Article Synopsis
- - The study analyzed soil selenium content and bioavailability in 1,985 soil samples and 120 crop/root samples from the Hetao Plain, revealing that about 5.59% of soil exceeded contamination risk values, but heavy metal levels in crops were low overall.
- - Selenium in the soil showed significant local enrichment and varied in availability, primarily influenced by natural factors; the forms of selenium were ranked by availability, with residues being the most available for plant absorption.
- - Key factors like soil texture, organic matter, and pH were found to influence selenium levels, where clay soil and high organic content could increase selenium accumulation but restrict its activity for plant uptake.
The geographical detector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. It can not only reveal the influence of a single factor on dependent variables but also evaluate the influence of two-factor interactions and does not need to consider linearity, while also avoiding the influence of multivariate collinearity. Without strong model assumptions, it solves the limitations of traditional methods in analyzing category variables.
View Article and Find Full Text PDFGeographic detectors can quickly detect spatial stratified heterogeneity and quantitatively reveal the intensity of driving factors of heavy metal content, which is of great significance for the prevention, control, and remediation of soil heavy metal pollution. In order to reveal the spatial differentiation and influencing factors of soil heavy metal content on the town-scale, 788 topsoil samples were collected from a town in the hinterland of Chengdu Plain. Soil heavy metal (Cd, Hg, As, Cu, Pb, Cr, Zn, and Ni) pollution risk assessments were carried out by using the geo-accumulation index method.
View Article and Find Full Text PDF