Dataset Information

Surface soil metal elements variability affected by environmental and soil properties.

ABSTRACT: Identifying the factors controlling the spatial variability of soil metal elements could be a challenge task due to the interaction of environmental attributes and human activities. This study aimed to investigate the critical explanatory variables controlling total Ca, Cd, Cr, Cu, Zn, Fe, Mn, Mg, Pb, and Zn variations in the arable topsoil using classical statistics, principal component analysis, and random forest techniques. The work was conducted in the core region of the Three Gorges Reservoir of China. The explanatory variables included soil, topography, climate, vegetation, land use type, and distance-related parameters. Average concentrations of the metal elements were in order of Fe > Mg > Ca > Mn > Zn > Cr > Ni > Pb > Cu > Cd. Soil Cr, Fe, and Pb showed low variability while others presented medium variability. Average concentrations of Cr, Fe, Cd, and Mg exceeded their corresponding background values. There were highly positive correlations between all metal elements except Pb, Cd and Cr. The principal component analysis further demonstrated that the sources of Pb, Cd, and Cr differed with other elements. The results of random forest suggested that soil properties followed by topography were critical parameters affecting the variations of Ca, Mg, Mn, Fe, Ni, Zn, and Cu. Agricultural activities and soil properties were major factors controlling the variations of Pb, Cr, and Cd. Further study should be conducted to understand the relations between the metal elements and soil properties.

SUBMITTER: Wu W

PROVIDER: S-EPMC8297850 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Mulching is widely used to increase crop yield in semiarid regions in northwestern China, but little is known about the effect of different mulching systems on the microbial properties of the soil, which play an important role in agroecosystemic functioning and nutrient cycling. Based on a 4-year spring maize (Zea mays L.) field experiment at Changwu Agricultural and Ecological Experimental Station, Shaanxi, we evaluated the responses of soil microbial activity and crop to various management systems. The treatments were NMC (no mulching with inorganic N fertilizer), GMC (gravel mulching with inorganic N fertilizer), FMC (plastic-film mulching with inorganic N fertilizer) and FMO (plastic-film mulching with inorganic N fertilizer and organic manure addition). The results showed that the FMO soil had the highest contents of microbial biomass carbon and nitrogen, dehydrogenase activity, microbial activity and Shannon diversity index. The relative use of carbohydrates and amino acids by microbes was highest in the FMO soil, whereas the relative use of polymers, phenolic compounds and amines was highest in the soil in the NMC soil. Compared with the NMC, an increased but no significant trend of biomass production and nitrogen accumulation was observed under the GMC treatment. The FMC and FMO led a greater increase in biomass production than GMC and NMC. Compare with the NMC treatment, FMC increased grain yield, maize biomass and nitrogen accumulation by 62.2, 62.9 and 86.2%, but no significant difference was found between the FMO and FMC treatments. Some soil biological properties, i.e. microbial biomass carbon, microbial biomass nitrogen, being sensitive to the mulching and organic fertilizer, were significant correlated with yield and nitrogen availability. Film mulching over gravel mulching can serve as an effective measure for crop production and nutrient cycling, and plus organic fertilization additions may thus have improvements in the biological quality of the soil and its sustainability in the rainfall-limited semiarid region.

Project description:Population size, genetic diversity, and performance have fundamental importance for ecology, evolution, and nature conservation of plant species. Despite well-studied relationships among environmental, genetic, and intraspecific trait variation (ITV), the influence of population size on these aspects is less understood. To assess the sources of population size variation, but also its impact on genetic, functional trait, and performance aspects, we conducted detailed population size estimations, assessed 23 abiotic and biotic environmental habitat factors, performed population genetic analyses using nine microsatellite markers, and recorded nine functional traits based on 260 Trifolium montanum individuals from 13 semi-dry grassland locations of Central Europe. Modern statistical analyses based on a multivariate framework (path analysis) with preselected linear regression models revealed that the variation of abiotic factors (in contrast to factors per se) almost completely, significantly explained fluctuations in population size (R 2 = .93). In general, abiotic habitat variation (heterogeneity) was not affected by habitat area. Population size significantly explained genetic diversity (N A: R 2 = .42, H o: R 2 = .67, H e: R 2 = .43, and I: R 2 = .59), inbreeding (F IS: R 2 = .35), and differentiation (G ST: R 2 = .20). We also found that iFDCV (ITV) was significantly explained by abiotic habitat heterogeneity, and to a lesser extent by genetic diversity H e (R 2 = .81). Nevertheless, habitat heterogeneity did not statistically affect genetic diversity. This may be due to the use of selectively neutral microsatellite markers, and possibly by insufficient abiotic selective pressures on habitats examined. Small T. montanum populations in nonoptimal habitats were characterized by reduced genetic and functional trait diversity, and elevated genetic inbreeding and differentiation. This indicates reduced adaptability to current and future environmental changes. The long-term survival of small populations with reduced genetic diversity and beginning inbreeding will be highly dependent on habitat protection and adequate land-use actions.

Dataset Information

Surface soil metal elements variability affected by environmental and soil properties.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets