ABSTRACT
Anhui, Henan, Jiangsu, and Shandong provinces were selected as the study area. A total of 599 soil samples and nine environmental factors of soil pH were collected. The spatial distribution of soil pH was modeled based on multi-scale geographically weighted regression(MGWR), mixed geographically weighted regression(Mixed GWR), geographically weighted regression(GWR), and multiple linear regression(MLR) models. Then, the spatial difference in the effect of environmental factors on soil pH was revealed using MGWR and quantile regression models. The results showed that:â soil pH showed significant global and local spatial autocorrelation at different spatial distances, and the clustering characteristics were obvious. â¡ The MGWR model was the best among the four models, and the Radj2 of MGWR, Mixed GWR, GWR, and MLR were 0.64, 0.62, 0.59, and 0.48, respectively. The residual of MGWR had the strongest independent distribution and the weakest spatial autocorrelation with a global Moran's I of 0.07. ⢠Three types of GWR predictions showed that the spatial distribution of soil pH decreased gradually from north to south in the study area, with the highest in northern Henan and the lowest in southern Anhui. ⣠MGWR modeling results showed that there was strong spatial heterogeneity of mean annual precipitation(MAP), multi-resolution valley bottom flatness(MRVBF), and elevation affecting soil pH. MAP had a stronger effect on soil pH in northern Jiangsu and most parts of Shandong. The positive effect of MRVBF on soil pH was stronger in northern Jiangsu and western Shandong. The negative effect of elevation on soil pH was stronger in northern and central Jiangsu. ⤠The quantile regression analysis showed that the mean annual precipitation had a significant negative effect on soil pH at different quantile levels of soil pH, and influence intensity decreased with the increase in pH quantile level. MRVBF had a significant negative effect on soil pH at a low quantile level(θ=0.1 to 0.4) but had no significant effect on soil pH at a high quantile level(θ=0.5 to 0.9). These results can provide an important reference for mapping soil properties and analyzing its influence factors based on the MGWR model in large regions.
ABSTRACT
To reveal the genetic characteristics of one member of the Plasmodium falciparum repetitive interspersed family (rif), we sequenced the rif gene (PF3D7_1254800) in 53 field isolates collected from Ghana-imported cases into China and compared them with 350 publicly available P. falciparum rif sequences from global populations. In the Ghana-imported population, the nucleotide diversities were 0.05714 and 0.06616 for the full length and variable region of rif gene, respectively. Meanwhile, 22 and 20 haplotypes were identified for the full length and variable region of rif gene (Hd = 0.843 and 0.838, respectively). Diversity of rif gene in Ghana-imported population was higher than that observed in Cambodia, Thailand, Vietnam, Myanmar, Mali, Ghana, and Senegal populations. In this analysis, we found high genetic diversity of rif gene in global P. falciparum populations and identified 158 haplotypes. Tajima's D-test shows that there are large differences in the direction of selection between the conserved and variable region of rif gene. Tajima's D value for the variable region was 0.20074, indicating that balancing selection existed in this region. We found that the variable region was the main target of selection for positive diversification, and most mutation sites were located in this region. The population structure suggested optimized cluster values of K =â¯6. The five groups in Ghana-imported population included a unique subpopulation. Our results reveal the dynamics of the rif gene (PF3D7_1254800) in P. falciparum populations, which can aid in the rational design of P. falciparum rif-based vaccines.
