Gradients in N-cycling attributes along forestry and agricultural land-use systems are indicative of soil capacity for N supply

Indicators of soil quality associated with N-cycling were assessed under different land-use systems (native forest NAT, reforestation with Araucaria angustifolia or Pinus taeda and agricultural use AGR) to appraise the effects on the soil potential for N supply. The soil total N ranged from 2 to 4 g/kg (AGR and NAT, respectively), and the microbial biomass N ranged from 80 to 250 mg/kg, being higher in NAT and A. angustifolia, and lower in P. taeda and AGR sites. Activities of asparaginase (ca. 50200 mg NH4+-N/kg per h), glutaminase (ca. 200800 mg NH4+-N/kg per h) and urease (ca. 80200 mg NH4+-N/kg/h) were also more intense in the NAT and A. angustifolia-reforested soils, indicating greater capacity for N mineralization. The NAT and AGR soils showed the highest and the lowest ammonification rate, respectively (ca. 1 and 0.4 mg NH4+-N/kg per day), but the inverse for nitrification rate (ca. 12 and 26%), indicating a low capacity for N supply, in addition to higher risks of N losses in the AGR soil. A multivariate analysis indicated more similarity between NAT and A. angustifolia-reforested sites, whilst the AGR soil was different and associated with a higher nitrification rate. In general, reforestation with the native species A. angustifolia had less impact than reforestation with the exogenous species P. taeda, considering the soil capacity for N supply. However, AGR use caused more changes, generally decrease in indicators of N-cycling, showing a negative soil management effect on the sustainability of this agroecosystem.

Correlation of soil microbial community responses to contamination with crude oil with and without chromium and copper

Soil microcosms contaminated with crude oil with or without chromium and copper were monitored over a period of 90 days for microbial respiration, biomass, and for dehydrogenase, lipase, acid phosphatase, and arylsulfatase activities. In addition, the community structure was followed by enumerating the total heterotrophic and oil-degrading viable bacteria and by performing a denaturing gradient gel electrophoresis (DGGE) of the PCR amplified 16S rDNA. A significant difference was observed for biochemical activities and microbial community structures between the microcosms comprised of uncontaminated soil, soil contaminated with crude oil and soil contaminated with crude oil and heavy metals. The easily measured soil enzyme activities correlated well with microbial population levels, community structures and rates of respiration (CO2 production). The estimation of microbial responses to soil contamination provides a more thorough understanding of the microbial community function in contaminated soil, in situations where technical and financial resources are limited and may be useful in addressing bioremediation treatability and effectiveness. (C) 2012 Published by Elsevier Ltd.

Spatial variability of soil fertility and its relationship with seed physiological potential in a soybean production area

The correlation of soil fertility x seed physiological potential is very important in the area of seed technology but results published with that theme are contradictory. For this reason, this study to evaluate the correlations between soil chemical properties and physiological potential of soybean seeds. On georeferenced points, both soil and seeds were sampled for analysis of soil fertility and seed physiological potential. Data were assessed by the following analyses: descriptive statistics; Pearson's linear correlation; and geostatistics. The adjusted parameters of the semivariograms were used to produce maps of spatial distribution for each variable. Organic matter content, Mn and Cu showed significant effects on seed germination. Most variables studied presented moderate to high spatial dependence. Germination and accelerated aging of seeds, and P, Ca, Mg, Mn, Cu and Zn showed a better fit to spherical semivariogram: organic matter, pH and K had a better fit to Gaussian model; and V% and Fe showed a better fit to the linear model. The values for range of spatial dependence varied from 89.9 m for P until 651.4 m for Fe. These values should be considered when new samples are collected for assessing soil fertility in this production area.