Biological ammonia oxidation had long been thought to be mediated solely by discrete clades of b-and c-proteobacteria (ammonia-oxidizing bacteria; AOB). However, ammonia-oxidizing Crenarchaeota (ammonia-oxidizing archaea; AOA) have recently been identified and proposed to be the dominant agents of ammonia oxidation in soils. Nevertheless, the dynamics of AOB versus AOA, and their relative contribution to soil ammonia oxidation and ecosystem functioning on stress and environmental perturbation, remain unknown. Using a 3-year longitudinal field study and the amoA gene as a molecular marker, we demonstrate that AOB, but not AOA, mediate recovery of nitrification after zinc (Zn) contamination. Pristine soils showed approximately equal amoA gene copy numbers and transcript levels for AOB and AOA. At an intermediate Zn dose (33.7 mmol Zn per kg), ammonia oxidation was completely inhibited, and the numbers of AOB and AOA amoA gene copies and gene transcripts were reduced. After 2 years, ammonia oxidation in the field soils was fully restored to preexposure levels, and this restoration of function was concomitant with an increase of AOB amoA gene copy and gene transcript numbers. Analysis of the restored community revealed domination by a phylogenetically distinct Zn-tolerant Nitrosospira sp. community. In contrast, the numbers of AOA amoA gene copies and gene transcripts remained 3-and 10 4 -fold lower than recovered AOB values, respectively. Thus, although recent findings have emphasized a dominant role of archaea in soil-borne ammonia oxidation, we demonstrate that a phylogenetic shift within the AOB community drives recovery of nitrification from Zn contamination in this soil.

Abstract-Two soil microbial processes, substrate-induced nitrification (SIN) and substrate-induced respiration (SIR), were measured in the topsoils of 12 Australian field trials that were amended separately with increasing concentrations of ZnSO4 or CuSO4. The median effect concentration (EC50) values for Zn and Cu based on total metal concentrations varied between 107 and 8,298 mg kg(-1) for Zn and 108 and 2,155 mg kg(-1) Cu among soils. The differences in both Zn and Cu toxicity across the 12 soils were not explained by either the soil solution metal concentrations or CaCl2-extractable metal concentrations, because the variation in the EC50 values was larger than those using total concentrations. Toxicity of Zn and Cu decreased with increasing soil pH for SIN. For Cu, also increasing cation exchange capacity (CEC) and percent clay decreased the toxicity towards SIN. In contrast to SIN, soil pH had no significant effect on toxicity values of SIR. Significant relationships were found between the EC50 values for SIR and background Zn and CEC for Zn, and percent clay and log CEC for Cu. Relationships such as those developed in this study will permit Australian environmental regulation to move from single-value national soil quality guidelines to soil-specific quality guidelines and permit soil-specific risk assessments to be undertaken.

SummaryRisk assessment of heavy metals in soil requires an estimate of the concentrations in the soil solution. In spite of the numerous studies on the distribution of Cd and Zn in soil, few measurements of the distribution coefficient in situ, K d , have been reported. We The E value ranged from 18 to 92% of the total metal content for Cd and from 5 to 68% for 3

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Abstract-Elevated metal concentrations in soils can disturb the soil ecosystem; thus, researchers strive to identify the most sensitive assay for detection of the early signs of toxicity. The purpose of the present study was to compare eight different ecotoxicological endpoints on the same set of metal-contaminated soils that were collected from seven series of soils sampled during field trials. The endpoints are based on three microbial assays (potential nitrification rate [PNR], substrate-induced respiration [SIR], and basal respiration [BR]) and two plant growth tests, one of which included symbiotic N fixation. The overall sensitivity of the endpoints to detect statistically significant adverse effects ranked as follows: PNR > SIR (lag time) > plant yield and N fixation > SIR (respiration after 24 and 48 h) > BR. The lowest adverse effect concentrations were found with the PNR at 7 mg kg(-1) of Cd and 107 mg kg(-1) of Zn. The variability of these endpoints among different uncontaminated soils was additionally assessed on 14 soil samples. That variability showed a strong correlation with sensitivity scores, illustrating that metal-sensitive endpoints have a large natural variability. We question the ecological relevance of highly sensitive microbial assays, because they tend to have a large natural variability. The identification of toxicity in the field requires endpoints that are highly sensitive and that do not vary greatly among soils (i.e., robust); however, no such endpoint was found in the present study. The endpoints that combined average sensitivity and robustness were SIR (lag time), clover yield, and N fixation in clover.

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Interest is mounting in developing and utilizing soil-specific soil quality guidelines. This requires quantifying the effects that soil physicochemical properties have on various ecotoxicological endpoints, including phytotoxicity. To this end, 14 agricultural soils from Australia with differing soil properties were spiked with copper (Cu) and zinc (Zn) salts and used to conduct 21-d plant growth inhibition tests using wheat (Triticum aestivum L.) in pot trials. The toxicity of Cu and Zn was similar with 10% effect concentration (EC10) values ranging from 110 to 945 and from 235 to 965 mg/kg, respectively, while the corresponding median effect concentration (EC50) values ranged from 240 to 1,405 and 470 to 1,745 mg/kg, respectively. Copper toxicity values (EC10, EC20, and EC50) were best modeled by the logarithm of cation exchange capacity (CEC) and either soil pH or electrical conductivity. Zinc EC50 and EC20 values were best modeled using the logarithm of CEC, while the EC10 data were best modeled using soil pH and the logarithm of organic carbon. These models generally estimated toxicity within a factor of two of the measured values.