The response of ammonia-oxidizing microorganisms to trace metals and urine in two grassland soils in New Zealand.

An incubation experiment was conducted to investigate the response of ammonia-oxidizing bacteria (AOB), ammonia-oxidizing archaea (AOA), and the nitrification rate to the contamination of Cu, Zn, and Cd in two New Zealand grassland soils. The soils spiked with different concentrations of Cu (20 and 50 mg kg-1), Zn (20 and 50 mg kg-1), and Cd (2 and 10 mg kg-1) were incubated for 14 days and then treated with 500 mg kg-1 urine-N before continuing incubation for a total of 115 days. Soils were sampled at intervals throughout the incubation. The nitrification rate in soils at each sampling period was determined, and the abundance of AOB and AOA was measured by real-time quantification polymerase chain reaction (qPCR) assay of the amoA gene copy numbers. The results revealed that moderate trace metal stress did not significantly affect the abundance of AOB and AOA in the two soils, probably due to the high organic matter content of the soils which would have reduced the toxic effect of the metals. Nitrification rates were much greater and the observable nitrification period was much shorter in the dairy farm (DF) soil, in which the AOB and AOA abundances were greater than those of the mixed cropping farm (MF) soil. AOB were shown to grow under high nitrogen conditions, whereas AOA were shown to grow under low N environments, with different metal concentrations. Therefore, nitrogen status rather than metal applications was the main determining factor for AOB and AOA growth in the two soils studied.

Modelling arsenic toxicity in wheat: simultaneous application of diffusive gradients in thin films to arsenic and phosphorus in soil.

The diffusive gradients in thin films (DGT) technique was evaluated in modelling wheat (Triticum aestivum) arsenic toxicity using a dataset of As-contaminated soil samples (n = 28) collected from former sheep dip sites. Above ground wheat biomass from a 21-day early growth bioassay was adopted as the response variable and the dose-response relationships were modelled using the three-parameter sigmoid equation. The DGT-derived effective soil solution As to P concentration ratios corresponded strongly to the differences in the response variable. With a single sample identified as an outlier, the 95% confidence interval for the effective soil solution As/P molar concentration ratio which resulted in a 50% reduction in the response (EC50) was 0.168-0.360. While the DGT-derived soil measure of As/P ratio was shown as a promising phytotoxicity predictor, the influence of P nutrition on the dose-response relationship deserves further consideration.

Adsorption of arsenate on soils. Part 2: modeling the relationship between adsorption capacity and soil physiochemical properties using 16 Chinese soils.

An attempt has been made to elucidate the effects of soil properties on arsenate adsorption by modeling the relationships between adsorption capacity and the properties of 16 Chinese soils. The model produced was validated against three Australian and three American soils. The results showed that nearly 93.8% of the variability in arsenate adsorption on the low-energy surface could be described by citrate-dithionite extractable Fe (Fe(CD)), clay content, organic matter content (OM) and dissolved organic carbon (DOC); nearly 87.6% of the variability in arsenate adsorption on the high-energy surface could be described by Fe(CD), DOC and total arsenic in soils. Fe(CD) exhibited the most important positive influence on arsenate adsorption. Oxalate extractable Al (Al(OX)), citrate-dithionite extractable Al (Al(CD)), extractable P and soil pH appeared relatively unimportant for adsorption of arsenate by soils.

Adsorption of arsenate on soils. Part 1: laboratory batch experiments using 16 Chinese soils with different physiochemical properties.

Laboratory batch experiments were carried out to study the adsorption of arsenate on 16 Chinese soils with different physicochemical properties. Wide differences in arsenate adsorption were observed, and the Jiangxi and Hubei soils were more effective sorbents for arsenate than other soils. The Langmuir one-surface and two-surface equations were used to model the arsenate adsorption data. Except for the Jiangxi and Hubei soils, the Langmuir one-surface equation gave reasonably good fits to the arsenate adsorption data. However, the Langmuir two-surface equation generally provided a better fit than the Langmuir one-surface equation. For soils with relative high organic matter (OM), dissolved organic carbon (DOC) or extractable phosphate, the Langmuir one-surface and two-surface equations described the adsorption isotherms similarly. In contrast, for soils with relatively low contents of OM, DOC or extractable phosphate, the Langmuir two-surface equation gave the better fit to the arsenate adsorption data.