Assessing the impacts of chemical cocktails on the soil ecosystem

Soil Biology & Biochemistry 75 (2014) 64e72

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Assessing the impacts of chemical cocktails on the soil ecosystem J. Horswell a, *, J.A. Prosser a, A. Siggins a, A. van Schaik a, L. Ying b, C. Ross c, A. McGill d, G. Northcott e a

Institute of Environmental Science and Research (ESR) Ltd, Kenepuru Science Centre, Porirua, New Zealand Plant and Food Research Ruakura, Private Bag 3230, Hamilton, New Zealand c Landcare Research, Palmerston North, New Zealand d Landcare Research, Hamilton, New Zealand e Northcott Research Consultants Ltd, 20 River Oaks Place, Private Bag 3200, Hamilton, New Zealand b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 26 November 2013 Received in revised form 12 March 2014 Accepted 18 March 2014 Available online 13 April 2014

Little is known about the environmental fate and effect of low levels of co-contaminants that are commonly present in wastes such as biosolids. Lysimeters were established using soils contaminated with Cu or Zn and augmented with triclosan. Triclosan degraded rapidly in the soils, with methyl-triclosan being the major degradation product. However, as metal concentration increased, transformation and biodegradation of triclosan decreased. For some soil health indicators (e.g. sulphatase enzyme), results suggested that general toxicity was increased when metals and triclosan were both present. These preliminary results suggest that co-contaminants can result in a combined effect that is potentially greater than the sum of the individual effects, with additional impacts on the rate and extent of contaminant degradation. Ó 2014 Elsevier Ltd. All rights reserved.

Keywords: Biosolids Triclosan Heavy metals Co-contaminants Soil health indicators

1. Introduction Triclosan (5-choloro-2-(2,4-dichlorophenoxy) phenol; TCS) is a broad spectrum antimicrobial agent, which is used in a wide variety of personal care products including deodorants, hand soaps, toothpaste, textiles, laundry detergents, antiseptics, shower gels and cleaning agents. Household products containing triclosan are typically discarded into the sewage system. The level of transformation and biodegradation of TCS in waste water treatment plants (WWTPs) varies with operating conditions (Xia et al., 2005). Some studies have shown >90% removal of TCS using activated sludge as secondary treatment (McAvoy et al., 2002; Bester, 2003; Kanda et al., 2003; Sabaliunas et al., 2003; Heidler and Halden, 2007). However, due to the hydrophobic nature (log Kow ¼ 4.8) of TCS, it is likely that a significant removal mechanism is sorption onto biosolids (McAvoy et al., 2002; Reiss et al., 2002). Both TCS and its transformation product methyl-TCS (5-chloro-2(2,4-dichlorophenoxy)-anisole) have been detected in surface waters downstream of sewage treatment plants (Lindstrom et al., 2002; Kookana et al., 2011). The limited data available in the

* Corresponding author. Tel.: þ64 4 9140684; fax: þ64 4 9140770. E-mail address: [email protected] (J. Horswell). http://dx.doi.org/10.1016/j.soilbio.2014.03.013 0038-0717/Ó 2014 Elsevier Ltd. All rights reserved.

literature suggests that the concentration of TCS in effluents can range from 35 ng L1 to 2700 ng L1 (McAvoy et al., 2002; Reiss et al., 2002; Singer et al., 2002; Sabaliunas et al., 2003; Halden and Paul, 2005). In a study of 19 effluents in Australia, Kookana et al. (2011), found concentrations of TCS ranging from 23 to 434 ng L1. A similar study of TCS in the influent and effluent of 13 WWTPs in New Zealand found TCS concentrations ranging from 25 to 100 ng L1 in the influent and 4.43e158 ng L1 in treated effluents (Strong et al., 2010). Concentrations of TCS in biosolids have been found to be an order of magnitude higher than in effluents ranging from 0.43 to 133 mg kg1 in the USA, (McAvoy et al., 2002; USEPA, 2009; Cha and Cupples, 2009); from 0.09 to 16.79 mg kg1 in Australia (Kookana et al., 2011) and 1.05e 17.23 mg kg1 in New Zealand biosolids (Speir and Northcott, 2006). A major pathway for the movement of organic contaminants such as TCS to the environment is through the land application of biosolids, a common practice in many countries (Lozano et al., 2012). Triclosan and other broad spectrum antimicrobial chemicals are specifically added to personal care products to prevent their deterioration by microorganisms. TCS targets numerous intracellular and cytoplasmic sites within cells, it may influence the transcription of genes participating in amino acid, carbohydrate and lipid metabolism (Reiss et al., 2009).

J. Horswell et al. / Soil Biology & Biochemistry 75 (2014) 64e72

It is these features that can unintentionally affect soil and aquatic animals should their habitats become contaminated with such chemicals. In a soil environment, previous studies have demonstrated inhibition of soil processes however, these are often short lived and the microbial community recovers (Waller and Kookana, 2009; Butler et al., 2011). Butler et al. (2011) measured both basal and substrate-induced respiration (SIR) in three soils types and found that TCS inhibited both parameters at concentrations as low as 10 mg/kg (in the loamy sand soil), however, both basal respiration and SIR recovered. Waller and Kookana (2009) also demonstrated TCS inhibited SIR in Australian sandy and clay soils. Their study demonstrated that TCS at concentrations below 10 mg/kg disturbed the nitrogen cycle in some soils (sandy soil; Waller and Kookana, 2009). Harrow et al. (2011) demonstrated changes in microbial numbers and community structure after irrigation of soils with greywater containing TCS. Impacts on microbial community structure were also found by Drury et al. (2013) in artificial streams. Biosolids contain a suite of contaminants including heavy metals, which can be present at concentrations significantly higher than organic compounds, primarily because they are not degraded by WWTP processes. Among the most prevalent of heavy metals in sewage are copper (Cu) and zinc (Zn), originating from both industrial and domestic sources (Smith, 1996). Copper and Zn therefore are the elements most likely to limit the amounts of treated sludge that can be applied to land (Smith, 1996). Heavy metal contaminants, present a risk to biological components of soil systems because of their persistence, toxicity to soil organisms and impairment of biological functions (Brookes and McGrath, 1984; Giller et al., 1998; Speir et al., 2007). What remains unknown is whether low concentrations of numerous compounds in biosolids combine to produce synergistic/antagonistic/additive ecotoxicological effects on ecosystems (Daughton and Ternes, 1999; Daughton, 2003; Dorne et al., 2007). As in other countries, current risk assessment procedures in New Zealand are reductionist, focussing on the fate and effects of individual chemicals and/or defined classes of chemicals in isolation from other contaminants present in biosolids. As a result, there is incomplete information about the environmental fate and effects of the complex cocktail of components in biosolids (e.g. nutrients, biological and chemical contaminants). Taking a first step to a holistic understanding of the toxicological effects and impacts of complex mixtures of contaminants is challenging, but is critical to assessing the potential risks that chronic low-level exposure may present to the environment. In this study we investigated the fate and effects of TCS in combination with copper or zinc in soil. We selected TCS as a model organic antimicrobial chemical to investigate the potential effects it may elicit on soil microbial activity and function in combination with the heavy metals Cu and Zn which are biologically active and found at high concentrations in wastes such as biosolids. An added complication to understanding the interaction of complex mixtures of contaminants in biosolids was illustrated by Speir et al. (2003, 2007) who postulated that responses of sensitive soil health indicators (such as enzymes) to potentially toxic elements can be masked by the effects of added organic matter (such as biosolids). Thus, in this study we avoided these confounding effects by using field soils historically contaminated with copper or zinc salts, and amending these with TCS spiked at 5 mg kg1 and 50 mg kg1, in the absence of biosolids. The degradation dynamics of TCS in the presence of increasing concentrations of heavy metals was measured, as well as changes in the soil microbial community. Effects of the co-contaminants on soil enzymes (phosphate and sulphatase), biomass and respiration, Most Probable Number Rhizobium, and the activity of sensitive microbial biosensors (Lux)

65

were measured as well as terminal restriction fragment length polymorphism (T-RFLP) bacterial community analysis. 2. Materials and methods 2.1. Experimental background and sample site The soil was obtained from an existing field trial, on a Horotiu sandy loam (a Vitric Orthic Allophanic Soil, Vitric Hapludand) at Ruakura, Hamilton, New Zealand (175 190 E, 37 470 S) (established April 2007). Soil physiochecmial properties are show in Table 1. The trial comprised 30 plots (1 m2), set out in two fullyrandomised replicate blocks. Each block contained seven plots amended with Cu, seven plots amended with Zn and a common unamended control plot. Prior to amendment, the top 100 mm of soil over the entire 1 m2 plot was removed and sieved (6.5 mm) to break up large clumps and remove vegetation (pasture species), then thoroughly mixed in a concrete mixer. Sulphate salts of Cu (CuSO4) or Zn (ZnSO4) were added to the mixing soil to raise metal concentrations and a basal dressing of superphosphate, (NH4)2SO4 and KCl was also mixed in at the same time. The amended soil was returned to its plot and packed down to its original field density. The plots were sown with a ryegrass/inoculated clover pasture seed mix. In 2010, three years after the trial was set up, approximately 15 kg of soil was collected from 11 of the plots to a depth of 10 cm sieved (2 mm) and stored at 4  C until required. The concentrations of Zn and Cu in the soils used for the current experiment are presented in Table 2. 2.2. Lysimeter construction Lysimeters were established in duplicate, with 33 treatments resulting in a total of 66 lysimeters. Each treatment contained a combination of varying concentrations of TCS and one of the heavy metals. Specifically, a range of five metal concentrations (Cu 101, 187, 478, 1083 and 2944 mg kg dry soil1; Zn 186, 283, 632, 1224 and 2235 mg kg dry soil1; Table 1). The range of metals were chosen in order to obtain high enough Cu and Zn concentrations in soil to sufficiently inhibit soil health indicators measured in this study (e.g. biomass and respiration) and allow accurate determination of dose response curves (covering previously determined EC 50 values for Cu and Zn, Speir et al., 2007). The metal spiked soils were combined with either 0, 5 (low) or 50 (high) mg kg1 TCS. Three control treatments containing no (or only background levels of) heavy metals, combined with 0, 5 or 50 mg kg1 TCS were also included in the study. The lysimeters were constructed from 15 cm lengths of PVC pipe (ø 13 cm). The base of the lysimeters contained a layer of gravel to retain the soil and assist drainage. Field moist sieved soil (1 kg) was adjusted to 65% water-holding-capacity (WHC) and spiked with TCS to obtain a final concentration of 0, 5 or 50 mg kg1 TCS. The spiking procedure was adapted from Brinch et al. (2002) to minimise the impact of organic solvents upon soil microbes. Briefly, 250 g field moist soil was distributed evenly on the base of a large shallow glass container. Either 3.56 mg or 35.57 mg of triclosan (for the 5 and 50 mg kg1 spiked soils respectively) was weighed into a glass vial and mixed with 20 mL of acetone. Using disposable glass Pasteur pipettes, the TCS-acetone solution was dripped evenly over

Table 1 Selected physiochemical properties of the Horotiu sandy loam. Total carbon (%)

Total Nitrogen (%)

pH (H2O)

CEC (cmol þ kg1)

11.6

1

5.4

39

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Table 2 Total Cu and Zn conc. of soils as analysed immediately prior to lysimeter construction. Treatment

Cu (mg kg dry soil1)

Zn (kg dry soil1)

Zero Cu1 Cu2 Cu3 Cu4 Cu5 Zn1 Zn2 Zn3 Zn4 Zn5

30 101 187 478 1083 2944 29 29 31 28 30

136 109 109 106 96 87 186 283 632 1224 2235

the surface of the 250 g portion of soil. After through mixing, the soil was left in the dark at room temperature overnight (16 h) to evaporate residual acetone. The TCS spiked soil was then mixed with the remaining 750 g of soil and packed into the lysimeters. The lysimeters were placed in a dedicated outdoor lysimeter facility and seated within a bed of pea gravel to within 1e2 cm of the top. The lysimeters were sown with ryegrass and irrigated when insufficient rainfall was observed. After 6 months, the lysimeters were harvested and analysed for a variety of chemical and biological indices. 2.3. Chemical and biological analyses Total Cu and Zn were measured on pressed discs of finely ground air-dry soil using X-Ray Fluorescence (XRF) spectrometry. Soil solution was extracted using the centrifugation method of Gillman (1976). After centrifugation, the resulting filtrate (soil solution) was collected and analysed for heavy metals by Inductively Coupled Plasma Mass Spectrometry (ICPMS). Soil pH and total C were determined according to Blakemore et al. (1987). Moisture content was determined by overnight drying at 105  C. Triclosan and degradation/transformation residues were extracted from the soil using Accelerated Solvent Extraction (ASE) with a mixture of dichloromethane/acetone (1:1) at 1500 psi and 100  C for 5 min. Each cell was extracted with two static cycles followed by a flush volume of 60% with the same solvent mix. The solvent extract was evaporated to dryness under a stream of nitrogen gas (Zymark Turbo-Vap) and redissolved in dichloromethane/methanol (95/5). An aliquot of the extract was cleaned up using florosil adsorption chromatography (Biotage Isolute 1 gm), evaporated to dryness, and derivatised by silylation using MTBSTFA and heating to 60  C for 30 min. Calibration standards containing the target compounds and internal standards were derivatised with each batch of individual samples. The resulting trimethylsylil esters were analysed by high resolution gas chromatography massspectrometry using an Agilent 6890N gas chromatograph (GC) coupled to an Agilent 5975A inert XL mass spectrometer (MS) and CTC autosampler. A 1 ml volume of derivatised sample extract was injected into an Agilent split/splitless injector at 280  C with a splitless time of 45 s and the components separated on a Varian Factor Four capillary column with 5% phenyl phase and integrated retention gap (40 m length; 0.25 mm film thickness; 0.25 mm ID) using a constant flow rate of helium (1 ml min-1). The column was held at 90  C for 1.5 min, increased at 20  C min1 to 150  C, with a second increase of 8  C min1 to 234  C, followed by a 6  C min1 increase to 280  C, and finally increasing at 20  C min1 to 330  C with a 5.5 min hold. The mass spectrometer interface temperature was maintained at 280  C, and ion source and quadrupole at 230  C and 150  C respectively. Compound specific mass fragments were obtained using single ion monitoring and were used in

combination with retention time matching for positive identification. The concentration of the three target analytes (TCS, methylTCS, and 2,4-dichlorophenol) was determined by extracting compound specific mass ions and comparing the relative abundance of the four mass ions against those obtained from pure compound standards. Quantification of target analytes was completed by internal standard quantitation using Agilent MSD Enhanced Chemstation quantitation software. Soil basal microbial respiration was determined by the gaschromatographic method of Sparling et al. (1986), using 12 g fresh weight soil and incubating for 7 d. Microbial biomass C was determined by the fumigation-extraction method of Vance et al. (1987), after adjusting the soil to 60% WHC, and using the modifications suggested by Sparling et al. (1990). Phosphatase and sulphatase enzyme activities were measured as reported by Speir et al. (1984), except that all assays contained 0.5 g soil, and phosphatase incubations were for 1 h only. Most-probable-numbers (MPN) of Rhizobium leguminosarum bv. trifolii were determined as in Speir et al. (2004) using the method first described by Vincent (1970). The bacterial bioassay, consisting of a lux-modified Escherichia coli biosensor, was conducted using the extracted soil solutions as described in Horswell et al. (2006). 2.4. Calculation of ecological dose parameters Soil biological properties, rhizobial MPN and lux-biosensor responses were related to total Zn and Cu concentrations using the sigmoidal dose response equation developed by CSIRO, Australia (Barnes et al., 2003; Smolders et al., 2004), based on the model developed by Haanstra et al., 1985. The equation is:

Y ¼

C 1 þ eðHðlog XlogEC50 ÞÞ

where Y is the biological activity; C is the calculated maximum value of Y; X is the metal concentration; EC50 is the metal concentration at which the biological activity is inhibited by 50%; and H is the Hill slope. Using this model, values were obtained for both EC50 and EC20 or Cu and Zn (mg kg dry soil1). 2.5. Terminal restriction fragment length polymorphism (T-RFLP) Total genomic DNA was extracted from 0.3 g of each of the 66 soil samples using the Mo Bio PowersoilÒ DNA Isolation Kit, following the manufacturer’s guidelines. DNA was eluted in 50 ml of Solution C6. The presence of genomic DNA was confirmed by agarose gel electrophoresis (2%) and quantified using a Quant-iTÔ PicoGreen dsDNA kit (Invitrogen). Bacterial 16S rRNA genes were amplified from each sample in triplicate with forward primer 63F (50 -CAG GCC TAA CAC ATG CAA GTC-30 ; Marchesi et al., 1998) and reverse primers 1087R (50 -CTC GTT GCG GGA CTT AAC CC-30 ; Hauben et al., 1997), which were labelled at the 50 end with the phosphoramidite dyes 6-FAM and VIC, respectively. PCRs were performed in 50 ml reactions containing: 5 ml 10  NH4 reaction buffer ((NH4)2SO4, 16 mM; TriseHCl [pH 8.8 at 25  C], 67 mM; 0.01% Tween-20); 3 mM MgCl2; 200 mM of dNTP (dATP, dTTP, dGTP, dCTP); 10 pmol of each primer; 0.5 U Taq polymerase and 2 ml of a 1:20 (v/v) dilution of extracted DNA in dH2O. The PCR reactions were carried out under the following conditions: Initial denaturation at 94  C for 3 min, then 30 cycles of: 94  C 30 s, 55  C 30 s, 72  C 60 s, followed by a final elongation step of 72  C for 20 min. Negative controls containing no DNA were used to screen for contamination. PCR products were visualised by UV excitation after electrophoresis on a 2% agarose gel.

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Triplicate PCR products were pooled during purification to reduce amplification bias and increase the DNA yield. Products were purified using the QIAquickÒ PCR purification kit (QIAGEN), and quantified using a Quant-iTÔ PicoGreen dsDNA kit (Invitrogen). Two hundred ng of each PCR product was digested with 20 U MspI in a final volume of 30 ml, containing 0.1 mg mL1 acetylated BSA (all Promega, UK). Restrictions were carried out in the manufacturers recommended buffer at 37  C for 3 h, followed by inactivation of the enzyme at 65  C for 20 min and storage at 4  C. Purification of restriction fragments was carried out using MinEluteÒ Reaction Cleanup kit (QIAGEN). The resulting fluorescent 50 and 30 terminal restriction fragments (T-RF’s) were quality checked by agarose gel electrophoresis before being sent for terminal fragment analysis (Massey Genome Service, Palmerston North, New Zealand) using an ABI3730 Genetic Analyser (Applied Biosystems, UK). The internal size standard LIZ GS500 (250) was added by the sequencing facility prior to peak quantification. The T-RFLP profile data was collated and analysed using the GeneMapper software v4.0. Fragments were included in further analysis if they were between 50 and 500 base pairs in length and were greater than 100 fluorescent units. The relative abundance of a T-RF in a profile was calculated as a proportion of the total peak height of all the T-RFs in that profile, and T-RFs that contributed less than 0.5% of the total peak height of a sample were also excluded from further analysis. Relative abundances for duplicate samples were averaged and these values were analysed using the PRIMER 6 (Plymouth Marine Laboratory) statistical package. After data were square-root transformed to satisfy assumptions of normality, they were subjected to non-metric multidimensional scaling (NMS), using a BrayeCurtis similarity matrix. Cluster analysis was performed on the T-RFLP data to identify groups of samples with 40, 60 and 80% similarity. 2.6. Statistical analysis The means and standard errors of ecological data were calculated using Excel 2012. Analysis of variance was performed using SPSS and the significance of difference assessed using Tukey posthoc tests at a 5% confidence level (p  0.05). 3. Results

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Fig. 1. Concentration of triclosan, methyl-triclosan and 2,4-dichlophenol (mg kg1) remaining after 6 months field ageing in the soils spiked with 5 mg kg1 triclosan and zinc at varying concentrations. Error bars represent standard errors. * indicates significant difference from control (p < 0.05).

3.2. Impacts of triclosan on soil health indicators Some of the measured biochemical properties demonstrated a significant (p < 0.05) impact upon exposure to TCS when combined with Cu or Zn (Figs. 5 and 6). This was particularly evident for sulphatase enzyme activity, which exhibited a significant reduction in the presence of TCS when combined with even the lowest concentration of Cu in soil (101 mg kg dry soil1) (Fig. 5). By comparison phosphatase enzyme activity was not significantly impacted by the presence of Cu until a ‘tipping point”, or threshold concentration was reached, upon which enzyme activity rapidly declined (Fig. 5). These results strongly suggest a possible synergistic effect of the presence of co-contaminants, highlighted by the fact that enzymes activity was not significantly reduced in the presence of TCS alone (Figs. 5 and 6) (control treatments). For the remaining soil health parameters (basal microbial respiration, microbial biomass C, rhizobial MPN and lux-biosensor) the presence of TCS caused either insignificant (large statistical error), or no effects above that which was evident from the presence of Cu and Zn alone.

3.1. Biodegradation of triclosan in soils Figs. 1e4 show the concentration of TCS, TCS methyl-ether and 2,4-dichlophenol remaining in lysimeter soils following 6 months ageing under field conditions. In the control soils containing either 5 or 50 mg kg1 TCS and no metals, TCS was rapidly degraded and <10% of the parent compound remained in the soils after 6 months. Rapid degradation of TCS was observed in all treatments, however, a distinction was observed at high metal concentrations. The major degradation product found in the soils was methyl-TCS (Figs. 1e4). As the soil concentration of both Zn and Cu increased, there was a reduction in both transformation and degradation of TCS in the soils. This was most evident for the highest Zn and Cu treatments, where significantly higher concentrations of TCS remained in soil compared to the control soils in three out of the four TCS treatments (Figs. 1, 3 and 4), and significantly less methyl-TCS was formed in the 50 ppm TCS treated soils (Figs. 2 and 4). Significantly less methyl-TCS was formed in the Zn þ 50 ppm TCS lysimeter soils above a Zn concentration of 283 mg kg dry soil1 (Fig. 2) and the concentration of 2,4-dichlophenol was significantly reduced by the presence of Zn in the Zn þ 5 ppm TCS treated soils compared to the control soil (Fig. 1).

Fig. 2. Concentration of triclosan, methyl-triclosan and 2,4-dichlophenol (mg kg1) remaining after 6 months field ageing in the soils spiked with 50 mg kg1 triclosan and zinc at varying concentrations. Error bars represent standard errors. * indicates significant difference from control (p < 0.05).

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J. Horswell et al. / Soil Biology & Biochemistry 75 (2014) 64e72

Fig. 3. Concentration of triclosan, methyl-triclosan and 2,4-dichlophenol (mg kg1) remaining after 6 months filed ageing in the soils spiked with 5 mg kg1 triclosan and copper at varying concentrations. Error bars represent standard errors. * indicates significant difference from control (p < 0.05).

3.3. Ecological dose parameters Effective concentrations that caused a 20% and 50% decline in activity (EC20 and EC50) were calculated for each metal, at all TCS concentration (0, 5 and 50 mg kg1; Tables 2 and 3). This analysis was undertaken to determine if the presence of an organic cocontaminant, in this case TCS, caused a reduction in the relative EC20 and EC50 for Zn or Cu, which would indicate increased toxicity as a result of exposure to a mixture of co-contaminants. Tables 3 and 4 show the Cu and Zn EC20 and EC50 values, calculated from the CSIRO dose response model using total metal concentrations of the soil samples. Most of the data demonstrated a good fit for the CSIRO model (high R2) and reliable EC values could be determined (e.g. lux biosensor, phosphatase and sulphatase), however some data did not exhibit a reasonable fit to the model (e.g. microbial biomass, respiration and rhizobium MPN). There are several possible explanations for this and these have been discussed at length by Speir et al. (2008). The most likely explanation with respect to this data set is the high variability within the data combined with small number of field replicates. As a result EC

Fig. 5. a) Sulphatase and b) Phosphatase enzyme activities in relation to total soil copper treatment in soil spiked with 0, 5 and 50 mg kg1 TCS. Error bars represent standard error. Values shareing the same letter are not significantly different (p < 0.05).

values can be calculated, but confidence intervals (statistical errors) are large. For the soils containing metals only, the calculated EC values were greater than the NZ Biosolids Guidelines soil limit concentration of 100 mg kg1 for Cu and 300 mg kg1 for Zn (NZWWA, 2003). However, there are instances where EC20 and/or EC50 values are close to this limit (sulphatase activity, microbial biomass, rhizobium MPN and the lux biosensor, Tables 3 and 4). In the soil treatments containing metals in combination with TCS some of the EC values decreased. For example the EC20 calculated for both sulphatase enzyme activity and the lux biosensor fell below the guideline limit for Zn when in the 50 mg kg1 TCS soil treatment (Table 4). For most of the measured soil health indicators, the presence of the co-contaminant TCS did not significantly impact the EC50 value. One exception was the lux biosensor, where soil solution extracted from Zn lysimeter soil spiked with 50 mg kg1 TCS, produced EC50 values significantly lower than the control soils (Table 4). In the Cu amended lysimeters, rhizobium MPN numbers in soil also appear to be reduced in the presence of increasing TCS, however the confidence intervals (statistical errors) vary greatly (Table 3). 3.4. The effect on microbial community structure

Fig. 4. Concentration of triclosan, methyl-triclosan and 2,4-dichlophenol (mg kg1) remaining after 6 months field ageing in the soils spiked with 50 mg kg1 triclosan and copper at varying concentrations. Error bars represent standard errors. * indicates significant difference from control (p < 0.05).

3.4.1. Terminal restriction fragment length polymorphism (T-RFLP) A total of 172 different T-RF’s were identified from the 33 samples after removal of peaks that did not meet the selection criteria previously outlined. Of these, 97 were from the 6FAM labelled 50 end of the gene fragment, with between 28 and 42 T-RF’s present in each sample. The remaining 75 T-RF’s were from the VIC labelled 30 end, with 27e42 detected in each sample.

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Table 4 The effective concentration (mg kg dry soil1) of Zn that caused 50% (EC50) and 20% (EC20) decline in activity of six soil health indicators, with and without TCS (at either 5 or 50 mg kg1). Values indicated with different letters were determined to be significantly different (p < 0.05). EC values noted with * are indicated to be below or close to the NZ guideline limits for soil Zn. Property Phosphatase

Fig. 6. Sulphatase enzyme activities in relation to total soil zinc treatment in soil spiked with 0, 5 and 50 mg kg1 TCS. Error bars represent standard error. Values shareing the same letter are not significantly different (p < 0.05).

Non-metric multidimensional scaling (NMS) analysis of T-RFLP relevant abundance profiles revealed that the bacterial community structure formed two distinct groups (A & B; Fig. 7). Statistical comparison of these two groups by ANOVA (SPSS) showed that they were significantly different (p < 0.05). The soil samples containing the highest level of copper (2944 mg kg1) grouped together (group A), while the remaining samples formed a distinct separate group (group B). Samples within each group demonstrated >80% similarity, while between 40 and 60% similarity was observed between the two groups (Fig. 7). The data did not indicate any combined effect of TCS and metal. 4. Discussion 4.1. Biodegradation of triclosan in soils containing Cu and Zn In all of the control treatments (no Cu or Zn) less than 10% of TCS remained in soil after 6 months. This was not unexpected due to the rapid degradation of TCS in soils- for example Kookana et al. (2011) and Liu et al. (2009) reported half-life of only 18 days for TCS in biologically active soils. In our study, the degradation of TCS was significantly reduced in the presence of Cu and Zn. At Cu concentrations of 2944 mg kg1, 29 and 26% of the applied TCS remained in soil after six months field ageing (5 mg kg1 and 50 mg kg1 Table 3 The effective concentration (mg kg dry soil1) of Cu that caused 50% (EC50) and 20% (EC20) declines in activity of six soil health indicators with and without TCS (at either 5 or 50 mg kg1). EC values noted with * are indicated to be below or close to the NZ guideline limits for soil Cu. Property Phosphatase

Treatment

0 ppm TCS 5 ppm TCS 50 ppm TCS Sulphatase 0 ppm TCS 5 ppm TCS 50 ppm TCS Lux biosensor 0 ppm TCS 5 ppm TCS 50 ppm TCS Microbial Biomass 0 ppm TCS 5 ppm TCS 50 ppm TCS Respiration 0 ppm TCS 5 ppm TCS 50 ppm TCS Rhizobium MPN 0 ppm TCS 5 ppm TCS 50 ppm TCS

EC50

EC20

R2

Lower 95% Upper 95%

1373 1355 1123 2092 1180 2480 1912 2033 2014 2179 922 1394 3226 3071 No fit 162 108* 46*

623 683 755 1133 308 2232 1483 1639 1181 1041 41* 510 2634 2695 e 145 82* 5*

0.965 0.971 0.962 0.979 0.969 0.869 0.997 0.997 0.998 0.858 0.766 0.891 0.685 0.674 e 0.856 0.928 0.741

991 1014 855 1756 630 1626 1683 1691 1913 1188 2 648 577 7 e 81 76 0

1903 1811 1474 2493 2208 3783 2173 2444 2120 4000 359,978 3000 18,029 1,360,688 e 325 152 87,716

Treatment

0 ppm TCS 5 ppm TCS 50 ppm TCS Sulphatase 0 ppm TCS 5 ppm TCS 50 ppm TCS Lux biosensor 0 ppm TCS 5 ppm TCS 50 ppm TCS Microbial Biomass 0 ppm TCS 5 ppm TCS 50 ppm TCS Respiration 0 ppm TCS 5 ppm TCS 50 ppm TCS Rhizobium MPN 0 ppm TCS 5 ppm TCS 50 ppm TCS

EC50

EC20

R2

Lower 95% Upper 95%

1900 3793 2818 2718 2488 3258 446a 511a 331b* No fit No fit 449 No fit No fit No fit No fit No fit 134*

716 1640 1401 961 711 257* 388a 350a* 227b* e e 78* e e e e e 103*

0.930 0.836 0.900 0.884 0.877 0.831 1.000 0.998 1.000 e e 0.821 e e e e e 0.826

1258 1419 1710 1399 1214 0 358 465 315 e e 19 e e e e e 37

2870 10,133 4644 5277 5100 22,355,157 554 561 347 e e 10,703 e e e e e 480

treated soils, respectively). This is likely due to inhibition of microbial degradation and transformation of TCS caused by the presence of heavy metals in the soil. Previous studies have noted that TCS degradation is significantly reduced (virtually eliminated) in sterile soil, highlighting the importance of microbial processes in the breakdown of TCS (Ying et al., 2007; Kookana et al., 2011). We hypothesise that the degradation and/or transformation of TCS has been inhibited in these soils where the microbial community has been previously compromised by prior exposure to the heavy metals Cu and Zn. The observed decrease of TCS in our lysimeter soil samples was mirrored by an increase in the concentration of the bacterial transformation product methyl-triclosan. The primary mechanism of degradation of triclosan in this study was biotransformation as microbially mediated degradation is the only known source of methyl-triclosan (Lindstrom et al., 2002). This is consistent with the results of Butler et al. (2012a) who identified methyl-triclosan to be the predominant metabolite resulting from the biodegradation of TCS in soils receiving biosolids. In our study the high Cu and Zn lysimeter soil treatments spiked with 50 mg kg1 TCS contained significantly lower concentrations of methyl triclosan compared to the control soil (Figs. 2 and 4). This result provides further evidence that the presence of high concentrations of Cu and Zn in the experimental soil inhibited the ability of the soil microbial community to metabolise TCS to the corresponding methyl ester. Given that previous research has demonstrated significant effects of TCS on biological parameters at levels as low as 10 mg kg1 (Butler et al., 2011) it is of significant concern that we had levels of TCS up to 13 mg kg1 remaining in Cu contaminated soils and up to 9 mg kg1 of TCS in Zn contaminated soils after six months. Indeed, Amorim et al. (2010) found that the reproduction EC10s for three soil invertebrate species were 0.6e7 mg TCS kg1 dry soil. Soil invertebrates were not investigated in our study, but the levels of TCS remaining in our soil samples were frequently higher than these, particularly those containing higher levels of Cu or Zn.

4.2. Effects of co-contaminants on soil health indicators The soil health indicators chosen for assessment are wellaccepted properties used to measure the environmental impact of soil contaminants (Speir et al., 2003). The addition of TCS to Zn and

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Fig. 7. NMS analysis plot of T-RFLP relative peak height data, calculated using the BrayeCurtis similarity index. “A” and “B” are two statistically significant clusters (p < 0.05).

Cu contaminated soils significantly reduced the activity of sulphatase and phosphatase enzymes. These reductions were most obvious for sulphatase enzymes, which exhibited a significant reduction in activity in soils containing Cu and TCS at relatively low levels (5 mg kg1 TCS, 187 mg kg1 Cu). However, TCS had no significant impact on the remaining soil properties above that which was observed from the presence of the metals alone. This may be due to the rapid degradation of TCS as mentioned previously, allowing many soil properties to recover over the 6 month experimental period. Previous studies have demonstrated inhibition of soil processes at TCS concentrations similar to those used in this study, however, these were often short lived and the microbial community recovered (Liu et al., 2009; Waller and Kookana, 2009; Butler et al., 2011). TCS has been previously demonstrated to inhibit both basal and substrate-induced respiration (SIR) (Liu et al., 2009; Waller and Kookana, 2009; Butler et al., 2011) in soil at concentrations as low as 10 mg kg1 and Liu et al. (2009) observed that TCS significantly inhibited soil respiration at TCS concentrations exceeding 10 mg kg1 (dry soil) during the first 4 days of incubation, but recovered after longer incubation. TCS disturbed the soil nitrogen cycle in an Australian sandy soil at concentrations below 10 mg kg1 (Waller and Kookana, 2009). The effect of TCS on soil enzyme activity is less definitive. Waller and Kookana (2009) did not observe any adverse effect of TCS on the activity of four soil enzymes (acid and alkali phosphotase, bglucosidase and chitinase). Liu et al. (2009) observed an initial impact of TCS on phosphatase activity at concentrations between 0.1 and 50 mg kg1 dry soil but this recovered after 2 days after which only minimal effects were observed. Given that our experiment did find an adverse effect of TCS on sulphatase and phosphatase activity it may be related to the combination of metal and TCS together. The adverse effect we observed

on soil sulphatase and phosphatase activity in our experiments occurred at concentrations of TCS that were within the range of previous studies (Liu et al., 2009; Waller and Kookana, 2009; Butler et al., 2011). The effects may be explained by combined impact of metals and TCS upon the soil microbial community, and the considerable difference in the incubation period between previous experiments (one to two weeks, Liu et al., 2009; Waller and Kookana, 2009) compared to the six month period of ageing in our study. Whilst some trends relating to the presence of TCS were observed in other soil properties measured in this study, these were not statistically significant. These trends may be better understood by carrying out further trials using a greater number of field replicates and including higher concentrations of TCS. 4.3. Ecological dose parameters For some of the soil health indicators we measured (sulphatase, MPN Rhizobium and lux biosensor) there was evidence that the presence of TCS as a co-contaminant acted to reduce the EC50/20 values for Zn and/or Cu to concentrations below those specified within the NZ Biosolids Guidelines. The nitrogen-fixing bacterium R. leguminosarum bv. trifolii is an economically vital component of New Zealand’s pastoral agriculture and indications that 50% of rhizobial viability (or even 20%) may be lost at Cu and or Zn concentrations around the current soil limit (NZWWA, 2003), and that this may be further reduced by the presence of TCS as co-contaminant is of concern. It is important to remember that the soils were amended with soluble metal salts, a potential worst case scenario that would directly expose soil organisms to a relatively higher proportion of bioavailable metal. However, the soils used in the current experiment were sampled

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three years after spiking, and it is likely that substantial proportions of the metals would have become bound to the soil and less bioavailable over time. There is evidence that this occurs when biosolids are spiked with metals salts (McLaren and Clucas, 2001), although the organic fraction of biosolids would be higher than in soil the same process would be likely to occur. 4.4. The effect of triclosan-metal co-contaminants on microbial community structure Analyses of microbial community structure using T-RFLP did not indicate any effect of TCS or TCS e heavy metal combined. The biggest influencing factor on microbial community structure appeared to be the highest Cu treatment, which grouped independently from the remaining samples based on NMS analysis. This result is in line with that of Butler et al. (2012b) who found that soil type and time were the most explanatory factors effecting microbial community structure in their experiment. In their study they found evidence of an effect of TCS on phenotypic responses, however, this was effectively masked by the influence of soil type. 4.5. Implications for environmental guidelines Although some research is available on the effects of TCS on soil ecological functions, little is known about the potential effect of low concentrations of numerous inorganic and organic chemicals present in biosolids (or other organic wastes) entering the soil environment. The results from this study have given valuable insight to the potential effect of TCS when combined with Cu or Zn on soil biological functioning. It has been shown that the mineralisation of TSC in soil is dependent on many factors, including soil chemistry, the existing microbial population, presence of oxygen, moisture, temperature and the form of the applied biosolids (Ying et al., 2007; Al-Rajab et al., 2009; Kookana et al., 2011; Butler et al., 2012a). Previous studies have found that the addition of biosolids to soil reduces the transformation of TCS (Kwon et al., 2010). Given that the current experiments were carried out without biosolids, this may pose a further risk of the accumulation of TCS in soil over time, particularly where co-contaminants are present and exert an inhibitory effect upon biodegradation/transformation processes. This raises concerns regarding the recycling of contaminant containing biosolids to land. Current risk assessment procedures focus on the fate of individual chemicals and do not consider the cumulative risk presented by mixtures of multiple low level co-contaminants. Future guidelines should acknowledge and take into account for the combination of chemicals present in organic wastes and develop new risk assessment procedures that incorporate thresholds for mixtures of chemical contaminants. 5. Conclusions This study has shown that the presence of heavy metal cocontaminants in soil can affect the microbial communities’ ability to degrade TCS and therefore increase its persistence and potential impacts on terrestrial organisms such as soil microbes. The preliminary data we have obtained from this experiment suggests the presence of co-contaminants in complex waste materials such as biosolids may combine to produce synergistic or additive ecotoxicological impact upon soil function and health indicators. The longer term impact of the combination of heavy metals and TCS upon these measures of soil function remains to be determined and will be the subject of future experiments.

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