Indicators of pesticide contamination: Soil enzyme compared to functional diversity of bacterial communities via Biolog® Ecoplates

European Journal of Soil Biology 47 (2011) 256e263

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European Journal of Soil Biology journal homepage: http://www.elsevier.com/locate/ejsobi

Original article

Indicators of pesticide contamination: Soil enzyme compared to functional diversity of bacterial communities via BiologÒ Ecoplates Carine Floch a, Anne-Céline Chevremont a, Karine Joanico a, Yvan Capowiez b, Stéven Criquet a, * a

Laboratoire d’Ecologie Microbienne IMEP, UMR CNRS 6116, Faculté des Sciences St Jérome, Service 452, Université Paul Cézanne-Aix Marseille III, Avenue Escadrille Normandie Niemen, 13397 Marseille Cedex 20, France b Institut National de Recherche Agronomique, UR 1115 “Plantes et Systèmes Horticoles”, Domaine Saint Paul, Site Agroparc, 84914 Avignon Cedex 9, France

a r t i c l e i n f o

a b s t r a c t

Article history: Received 17 December 2010 Received in revised form 26 May 2011 Accepted 27 May 2011 Available online 1 July 2011 Handling editor: Christoph Tebbe

The aim of this study was to clarify the potential of soil enzyme activities as indicators of pesticide contamination, and to compare this to using the functional diversity of bacterial communities via BiologÒ Ecoplates. The individual effects of the pure active ingredients (i.e. not the commercial formulations) of ten pesticides on various soil enzyme activities were recorded under laboratory conditions at different incubation times (i.e. 0, 2, 6 and 12 months). Results clearly showed that response patterns of soil enzyme activities differed in their sensitivities to pesticide addition over time (i.e. stimulation, inhibition or no effect). Results suggested that phenol oxidase activity could be used as an early indicator of pesticide contamination, and arylamidase and b-glucosidase could be used to evaluate soil resilience after pesticide disturbances. We concluded that the functional diversity of bacterial communities was less efficient than soil enzyme activities as an indicator of pesticide contamination. Ó 2011 Published by Elsevier Masson SAS.

Keywords: BiologÒ Bacterial functional diversity Indicator of soil contamination Microcosms Pesticides Soil enzymes

1. Introduction Pesticides, including fungicides, herbicides and insecticides, are widely used in agroecosystems to improve crops. Since the 1950’s, intensive farming methods have increased the range and effects of these agrochemicals. Once a pesticide is released into soil matrix, its effect will depend both on its characteristics and on those of the soil [20]. Reactivity with the soil biological compartment is one of the principal interactions between soil constituents and pesticides, which are known to be microbially degraded or mineralized by telluric fungi [24,28] and bacteria [14,27]. Indeed, soil microorganisms have enzyme pools which allow them to degrade both natural and xenobiotic substrates. However, while microorganisms control to the fate of pesticides in soils, pesticides can have a negative effect on their activities [39]. In 2005, the French Agency for the Environment and Energy Management (ADEME) launched a national research program “Bioindicators of soil quality”. Its principal aim was to develop sensitive and appropriate indicators of soil contamination. Soil

* Corresponding author. Tel.: þ33 4 91 28 85 30; fax: þ33 4 91 28 81 90. E-mail address: [email protected] (S. Criquet). 1164-5563/$ e see front matter Ó 2011 Published by Elsevier Masson SAS. doi:10.1016/j.ejsobi.2011.05.007

enzyme activities have been suggested as potential indicators of soil use and management because of their relationship to soil biology [42], and it is generally assumed that the biological properties of soil, such as enzyme activities, are earlier indicators of soil degradation than chemical or physical parameters [13]. In addition, many soil enzyme assays are ideal for this purpose, being relatively simple, rapid and cost effective. Our aim herein was thus to assess the potential of soil enzyme activities as indicators of soil contamination with pesticides, and to compare their efficiency to that of the functional diversity of bacterial communities via BiologÒ Ecoplates. With this aim, experiments were performed under laboratory conditions using microcosm incubations. Microcosms are currently used in soil ecology principally to evaluate the environmental impacts of a contaminant on microbial communities [8,40]. Such experimental approaches offer opportunities to study a wide range of parameters. Moreover, abiotic factors such as temperature and moisture can easily be controlled, in order to focus on biotic interactions. Pesticides (i.e. 2,4D, atrazine, azinphos-methyl, carbaryl, diuron, glyphosate, linuron, mancozeb, parathion-methyl and prometryne) were selected on the basis of: i) wide use in agroecosystems and, ii) high input to both surface and ground waters [2,30]. Enzyme activities were selected because of their critical role in C (cellulase,

C. Floch et al. / European Journal of Soil Biology 47 (2011) 256e263 Table 1 Chemical and biological classifications of pesticides. No

Common name

Chemical classification

Biological classification

1 2 3 4 5 6 7 8 9 10

2,4D Carbaryl Mancozeb Glyphosate Azinphos-methyl Parathion-methyl Atrazine Prometryne Diuron Linuron

Aryloxyacid Carbamate Carbamate Organophosphosphate Organophosphosphate Organophosphosphate Triazine Triazine Urea Urea

Herbicide Herbicide Fungicide Herbicide Acaricide Insecticide Herbicide Herbicide Herbicide Herbicide

fluorescein diacetate hydrolase, b-galactosidase, b-glucosidase, phenol oxidase,), N (arylamidase), P (acid and alkaline phosphomonoesterases, phosphodiesterase and phosphotriesterase) and S (arylsulfatase) biogeochemical cycles and nutrient mineralization processes. In parallel, functional diversity was investigated to determine pesticide effects on bacterial communities via BiologÒ Ecoplates.

257

the commercial formulation. All pesticides were purchased from Sigma (St Louis, USA). The chemical and biological classifications of the pesticides are given in Table 1. 2.3. Microcosms Microcosms were prepared in plastic boxes of 5 cm  5 cm  5 cm. Each microcosm contained 100 g of dry weight equivalent soil and 100 ppm of a single pesticide (100 mg pesticide per g soil) supplied as powder and homogenized manually using a rotator (Manual miniinversina, Bioengineering). Soil microcosms without pesticide were used as controls. Water content was adjusted to 60% of the maximum water-holding capacity (WHC) to standardize moisture levels. This WHC was maintained by weighting soil every 3 days using sterile distilled water in order to compensate for any weight loss. During experiments, all microcosms were incubated in darkness at 25  1  C. Three replicates were performed for each sampling time and pesticide treatment, for a total of 132 samples. Samples were collected at time 0 (2 days), 2, 6 and 12 months after pesticide addition using the destructive method. At every sampling, 3 replicates from each microcosm type were randomly chosen and were analyzed separately.

2. Materials and methods 2.4. Enzyme assays 2.1. Soil samples The soil used for the microcosm study was collected in an abandoned apple orchard in Monfavet close to Avignon (Vaucluse region, France) located at 43 530 5200 N, 4 540 0500 E in February 2007. This soil was chosen because it was not exposed to pesticides for over 20 years. The soil characteristics were determined by the Soil Analysis Laboratory (LAS) from INRA (Arras, France) and were: organic carbon 7.7 g kg1 soil, nitrogen Kjeldahl 1.18 g kg1 soil, organic matter 13.4 g kg1 soil and pH 8.3. The soil texture was 23.4% clay, 57% silt and 19.3% sand. Soil was sampled by randomly pooling five subsamples from a 0e20 cm soil depth. Prior to use, soil was sieved through a 2 mm mesh and dry weight was determined after drying 1 g of soil at 100  C in an oven for 24 h. 2.2. Pesticides Pesticides used were 2,4D ((2,4-dichlorophenoxy)acetic acid), atrazine (6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-di amine), azinphos-methyl (S-3,4-dihydro-4-oxo-1,2,3-benzotriazin-3ylmethyl O,O-dimethyl phosphorodithioate), carbaryl (1-naphthyl methylcarbamate), diuron (3-(3,4-dichlorophenyl)-1,1-dimethyl urea), glyphosate (N-(phosphonomethyl)glycine), linuron (3-(3,4dichlorophenyl)-1-methoxy-1-methylurea), mancozeb (manganese ethylenebis(dithiocarbamate) (polymeric) complex with zinc salt), parathion-methyl (O,O-dimethyl O-4-nitrophenyl phosphorothioate) and prometryne (N2,N4-diisopropyl-6-methylthio-1,3,5-triazine-2,4diamine). The active ingredient of each pesticide was applied, not

The enzyme activities assayed were arylamidase, arylsulfatase, cellulase, fluorescein diacetate hydrolase, b-galactosidase, b-glucosidase, phenol oxidase, alkaline and acid phosphomonoesterases, phosphodiesterase and phosphotriesterase. The corresponding methods used are presented in Table 2. The method of Green et al. [23] was modified to monitor fluorescein diacetate hydrolase activity; the pH buffer used was 7.0 instead of the 7.6 recommended by Alarcon-Gutiérrez et al. [3], to avoid potential non-enzymatic interferences. Enzyme assays were performed in 3 replicates for each soil sample. A unit (U) of enzyme activity was defined as mmole of substrate hydrolyzed or oxidized min1, and per g of soil dry weight (U g1 DW). For each incubation time, enzyme activity values of non-treated soils were taken as a reference point and subtracted from those of treated soils. As a consequence, enzyme activities were scaled against control values illustrated on the different figures by the x axis. Indeed, a similar approach has previously been used with success by Sannino and Gianfreda [29] to illustrate these kinds of results. Thus, negative activities indicate an enzyme inhibition by pesticides, whereas positive activities indicate enzyme stimulation by pesticides. 2.5. Bacterial functional diversity Bacterial functional diversity was studied via BiologÒ Ecoplate. Briefly, 10 g of soil was added to 100 ml of a sterile sodium pyrophosphate solution (0.1%) in a 250 ml flask and was shaken at

Table 2 Methods used for enzyme assays. Enzyme activity

Catalytic reaction

Substrate

Reference

Arylamidase Arylsulfatase Cellulase Fluorescein diacetate hydrolase b-galactosidase b-glucosidase Phenol oxidase Alkaline phosphomonoesterases Acid phosphomonoesterases Phosphodiesterase Phosphotriesterase

Amino acid hydrolysis Sulfoester hydrolysis Cellulose hydrolysis Ester hydrolysis Saccharide hydrolysis Cellobiose hydrolysis Aromatic compound oxidation Phosphomonoester hydrolysis Phosphomonoester hydrolysis Phosphodiester hydrolysis Phosphotriester hydrolysis

Hydrochloride L-leucine b-naphtylamide p-Nitrophenyl sulfate Carboxymethylcellulose Fluorescein diacetate p-Nitrophenyl b-D-galactopyranoside p-Nitrophenyl b-D-glucopyranoside ABTS p-Nitrophenyl phosphate p-Nitrophenyl phosphate Bis p-nitrophenyl phosphate Tris p-nitrophenyl phosphate

[1] [38] [12] [3,23] [17] [17] [18] [36] [36] [16] [16]

8

Fluorescein diacetate hydrolase

∗

∗

∗

-1

4 0 -4

∗

-8

∗

-12

∗

∗

∗

∗ ∗

1

2

3

4

0 month

∗

∗

5

6

2 months

7

∗

8

6 months

9

10

12 months

β-Galactosidase

∗

0,5

-1

200 rpm for 20 min. The resulting mixture was diluted about 100fold with a sterile NaCl solution (0.85%). According to the protocol defined by Calbrix et al. [9], the dilution was adjusted to obtain a pre-defined concentration of microbial cells. Thereafter, the dilution was used to inoculate wells of the BiologÒ Ecoplate. Plate was incubated at 25  C and absorbance at 595 nm was measured daily for 7 d. Metabolism of the different substrates in the wells resulted in the reduction of tetrazolium, which changed from colorless to purple formazan. The absorbance value of the BiologÒ Ecoplates control well (containing no substrate), filled with the 100-fold soil dilution, was subtracted from the absorbance of every other wells, to eliminate background color from the soil suspension. The average well-color development (AWCD0.5) value was calculated for each well separately, as first described by Garland and Mills [19]. Thereafter, and as suggested by Preston-Malfham et al. [26], AWCD0.5 values of substrates were assigned to guilds (i.e. amino acids, amides/amines, carbohydrates, carboxylic acids, miscellaneous and polymers) and used to express the results of bacterial functional diversity. As previously described for soil enzyme activities, AWCD0.5 values of non-treated soils were taken as a reference point at each incubation time (see Section 2.4).

Activity (mU.g DW)

C. Floch et al. / European Journal of Soil Biology 47 (2011) 256e263

Activity (mU.g DW)

258

0,0 ∗

-0,5

∗

∗

∗

∗

-1,0 1

2

3

4

0 month

5

6

2 months

7

6 months

8

9

10

12 months

∗

∗

∗

∗

∗

∗

Pesticide effects on soil enzyme activities and on functional diversity of bacterial communities over time were tested by oneway repeated measures ANOVA’s. The post-hoc Tukey’s honestly significant difference (HSD) tests were performed in complement, to test for the significant differences between treated soils and

0 ∗

-5

1

2

∗

3

∗

4

0 month

-1

Activity (mU.g DW)

Arylamidase ∗

10

∗

∗

∗ ∗

-20 ∗

1

∗

2

∗

3 0 month

∗ ∗

4

∗

∗

∗

5

2 months

7

6 months

∗

8

9

12 months

-1

∗

0

-1 1

∗

∗

∗

∗∗

2

3

∗

∗

4

0 month

∗ ∗

5

2 months

∗

6

∗

∗

∗

7

6 months

∗

8

9

∗

10

-1

Activity (mU.g DW)

∗

∗

∗

∗

∗

0 ∗

-10 1

∗

2

3 0 month

4

5 2 months

6 6 months

8

9

10

12 months

3. Results

20 ∗

7

3.1. Soil enzyme activities

12 months

30

∗

6 6 months

∗

Cellulase

10

5 2 months

∗∗

∗

control soils without pesticide at each incubation time at 5% (P < 0.05). All these statistical analyses were performed using STATISTICA software version 6.1 (Statsoft, France). Principal component analyses (PCA) were performed to compare pesticide effects over time on microbial parameters using XLSTAT software version 2006 (Addinsoft, France) and SigmaPlot software version 8.2 (SPSS, Chicago).

10

Arylsulfatase

1

∗

∗ ∗

6

∗

Fig. 2. Effect of pesticides on fluorescein diacetate hydrolase, b-galactosidase and bglucosidase activities of soil at different incubation times. For treatments, see Table 1. Error bars represent the standard error of mean of three replicates (n ¼ 3). (*) Symbols indicate significant difference from control without pesticide for each incubation time (Tukey’s HSD test, P < 0.05).

∗

0 -10

-30

Activity (mU.g DW)

∗

∗

∗

∗

-1

2.6. Statistical and multivariate analyses

Activity (mU.g DW)

β-Glucosidase 5

7

∗

∗

8

9

10

12 months

Fig. 1. Effect of pesticides on arylamidase, arylsulfatase and cellulase activities of soil at different incubation times. For treatments, see Table 1. Error bars represent the standard error of mean of three replicates (n ¼ 3). (*) Symbols indicate significant difference from control without pesticide for each incubation time (Tukey’s HSD test, P < 0.05).

Pesticide effects on soil enzyme activities during incubation are shown in Figs. 1e4. The highest variability in soil enzyme responses to the presence of pesticides was observed for phenol oxidase activity, from 2.27 to 55.32 mU g1 DW. By contrast, the lowest variability was observed for phosphotriesterase activity, from 0.31 to 0.30 mU g1 DW. Analyses of variance (One-way repeated measures ANOVA’s) showed that, in most cases, individual pesticides had significant effects on soil enzyme activities over time. However, in some cases they had no significant effects throughout the incubation time (Table 3). For example, 2,4D did not affect the activity levels of arylamidase, arylsulfatase, cellulase, acid phosphomonoesterase and phosphodiesterase over time. In most cases, results showed immediate effects following pesticide addition (i.e. 2 d called to 0 month). Indeed, for

C. Floch et al. / European Journal of Soil Biology 47 (2011) 256e263

-1

Activity (mU.g DW)

Phenol oxidase ∗

50 40 30 20 10 0 -10

1

2

3

4

5

0 month

6

2 months

7

8

6 months

9

10

12 months

∗

∗

∗

∗

-1

Activity (mU.g DW)

Acid phosphomonoesterase 6

∗

3 0 ∗

∗

-3 1

2

3

4

5

0 month

6

2 months

∗

7

8

6 months

9

10

12 months

-1

Activity (mU.g DW)

Alkaline phosphomonoesterase 15

∗

10

∗

∗

∗

5 0 -5

∗

∗

∗

∗

∗

-10 1

2

3

4

5

0 month

6

2 months

7

6 months

8

∗

∗

9

10

12 months

Fig. 3. Effect of pesticides on phenol oxidase, acid and alkaline phosphomonoesterase activities of soil at different incubation times. For treatments, see Table 1. Error bars represent the standard error of mean of three replicates (n ¼ 3). (*) Symbols indicate significant difference from control without pesticide for each incubation time (Tukey’s HSD test, P < 0.05).

arylamidase, b-glucosidase, acid phosphomonoesterase, alkaline phosphomonoesterase and phosphotriesterase activities, pesticides generally had an immediate stimulating effect (8 of 10). In contrast, there was usually (except for 2,4D and diuron) an

-1

Activity (mU.gDW)

∗

0 ∗

∗

-3

1

2

∗

∗

∗

3

4

∗

∗

∗

∗

5

0 month

2 months

6

7

6 months

8

9

10

12 months

Phosphotriesterase ∗

∗∗

∗

-1

Activity (mU.gDW)

0,5

∗

∗

∗

∗

0,0 ∗

-0,5

immediate and generally significant inhibiting effect of pesticides on arylsulfatase activity. For the other soil enzymes (i.e. cellulase, fluorescein diacetate hydrolase, b-galactosidase, phosphodiesterase), activities at the initial time showed more erratic fluctuations, being stimulated, inhibited or unaffected (40%, 45% and 15% of the different pesticides respectively) depending on the pesticide tested. Finally, phenol oxidase was the sole enzyme showing no response in its activity at the initial incubation time (0 month covering to 2 day) whatever the pesticide. During incubation (0e12 months), the fluctuation patterns of some soil enzyme activities were similar. After an immediate initial increase, arylamidase and b-glucosidase activities generally decreased between 0 and 6 months’ incubation and finally tended to return to their initial soil background levels after 12 months’ incubation. A quite different effect was observed for phenol oxidases, whose activities generally increased after 2 months’ incubation, and thereafter returned to their initial soil background levels only after 6 months’ incubation (i.e. more quickly than the other enzymes). With some exceptions, after 12 months’ incubation arylsulfatase and b-galactosidase activities were still considerably inhibited. The other soil enzyme activities showed erratic up-and-down fluctuations from controls during incubation. In order to reduce the dimensionality of the data set, a principal component analysis (PCA) was performed to compare pesticide effects over time on soil enzyme activities (Fig. 5). The first principal component (PC1) and the third principal component (PC3) explained respectively 28.77% and 14.71% of the total variability (19.81% for PC2, data not shown). PCA plots clearly illustrated how soil enzyme activity pools changed with time. Arylamidase and b-glucosidase activities explained respectively 26.77% and 16.19% of the PC1 variability corresponding to samples at 0 and 12 months’ incubation. Samples at 2 months’ incubation principally showed cellulase, phenol oxidase and phosphodiesterase activities. Arylsulfatase and alkaline phosphomonoesterase activities were principally observed at 6 months’ incubation. The similarity among samples at the beginning (0 month) and at the end (12 months) of the incubation time along PC1 can be interpreted as the gradual return of soil enzyme activity pools to their initial soil background level after 12 months’ incubation (as also indicated by the circle arrow on Fig. 5). 3.2. Bacterial functional diversity

Phosphodiesterase

3

259

1

2

3 0 month

4

∗

∗

∗ ∗

∗

5 2 months

6 6 months

7

8

9

10

12 months

Fig. 4. Effect of pesticides on phosphodiesterase and phosphotriesterase activities of soil at different incubation times. For treatments, see Table 1. Error bars represent the standard error of mean of three replicates (n ¼ 3). (*) Symbols indicate significant difference from control without pesticide for each incubation time (Tukey’s HSD test, P < 0.05).

Bacterial functional diversity was studied, to determine the effect of pesticides on indigenous soil bacterial communities via BiologÒ Ecoplates, and utilization patterns of each substrate guild were considered separately (Figs. 6 and 7). As for soil enzyme activities, AWCD0.5 values varied over time depending on pesticide considered (Figs. 6 and 7). However, results from one-way repeated measures ANOVA’s (Table 4) globally showed that amines/amides and polymers were the substrates the more significantly affected by pesticide treatments over time. In contrast, utilization patterns of the other substrate guilds were the less affected and, in the case of carboxylic acids, no one significant effect was detected over incubation time. Fig. 8 compares BiologÒ Ecoplates utilization patterns of each substrate guild (i.e. amino acids, amides/amines, carbohydrates, carboxylic acids, miscellaneous and polymers) over time, using PCA. The first principal component (PC1) and the second principal component (PC2) explained respectively 32.66% and 19.41% of the total variability. PCA plots indicated that bacterial functional diversity changed with time. However, utilization patterns of all substrate guilds were characteristic of soil samples at 2 months’ incubation, indicating a higher bacterial functional diversity at this time than at 0, 6 and 12 months’ incubation. Moreover, the similarity among

260

C. Floch et al. / European Journal of Soil Biology 47 (2011) 256e263

Table 3 Results of one-way repeated measures ANOVA’s from enzyme activities. Symbols indicate significant differences from control without pesticide addition over time (Tukey’s HSD test. *: P < 0.05; **: P < 0.01; ***: P < 0.001). Enzyme activity

Pesticide

Enzyme score (%)

1

2

3

4

5

6

7

8

9

10

Arylamidase Arylsulfatase Cellulase Fluorescein diacetate hydrolase b-Galactosidase b-Glucosidase Phenol oxidase Acid phosphomonoesterase Alkaline phosphomonoesterase Phosphodiesterase Phosphotriesterase

ns ns ns 8.65*** 10.34*** 3.68* 22.74*** ns 8.98*** ns 9.81***

9.61*** 8.45*** 4.74* 9.09*** ns 10.97*** 10.99*** 5.74** 2.85* 5.78** 4.07*

6.38** 4.18* 8.56** 4.25* ns 8.47*** ns 4.01* 7.94*** ns 3.96*

13.71*** 5.86** ns 9.86*** 3.07* 6.19** 5.91** 7.12** 5.31** 8.36** 10.18***

13.72*** 7.25** 7.50** 9.47*** ns 14.82*** ns 3.72* 3.05* ns 4.22*

23.27*** 12.45*** ns 13.56*** ns 15.38*** ns 13.66*** 17.45*** ns ns

ns ns ns 4.83** ns 4.17* 5.95** 3.91* ns 8.40*** 3.82*

23.96*** 8.49*** ns 11.05*** 2.99* 23.04*** 5.19** 6.31** 7.12** 3.98* 12.51***

ns 8.48*** 10.54*** 5.15** 9.83*** ns ns ns 8.72** ns 5.02*

10.01*** 5.91** ns 36.17*** ns 35.59*** ns 8.44*** 5.12** 3.12* 12.57***

Pesticide score (%)

55

91

73

91

73

55

55

91

55

73

70 80 40 100 60 90 50 80 90 50 90

Scores give the % of significant effects when considering “all pesticides vs each enzyme (enzyme score)” or “each pesticide vs all enzymes (pesticide score). For pesticide treatments, see Table 1.

samples from the beginning (0 month) and the end (6 and 12 months) of the incubation with pesticides could be ascribed to a return of microbial communities to their initial composition, in other words to soil resilience (indicated by the circle arrow on Fig. 6).

time (12 months) parameters were selected to approach conditions encountered under field conditions in agroecosystems with phytosanitary treatment.

4. Discussion

Results clearly showed that soil enzyme activities differ in their sensitivity to pesticide addition. Indeed, both significant positive and negative responses, as well as no significant responses, were recorded compared to non-treated soil controls. Several explanations can be given for the significant variations observed. Direct and indirect effects of pesticides on soil enzyme activities may occur simultaneously. As mentioned by Tabatabai [37], pesticides may directly interact with soil enzymes by binding with the active

Amides/Amines 1

AWCD 0.5

The aim of this study being to determine whether some soil enzymes are reliable bioindicators of soil functioning following pesticide contamination; microcosm experiments were performed to investigate both type of pesticide and incubation time effects on soil microbial parameters. Because of potential interference during enzyme assays when pesticides are added to soil dissolved in organic solvents such as methanol [21], we chose to add pesticides to soil in the form of powders. Although, it is generally assumed that chemicals affect soil enzyme activities in a concentrationdependent manner, we chose to study a single pesticide concentration to allow comparison of the effects of different pesticides. Moreover, pesticide concentration of 100 ppm, a concentration commonly used in soil ecotoxicological studies [34], and incubation

4.1. Direct and indirect effects of pesticides on soil enzyme activities

0

-1

1

2

3

4

5

0 month

6

7

6 months

8

9

10

9

10

12 months

Amino acids

1

AWCD 0.5

2 months

0

-1

1

2

3

4

5

0 month

2 months

6

7

6 months

8

12 months

Carbohydrates AWCD 0.5

1

∗

0 ∗

-1 1

2

3

4 0 month

Fig. 5. Principal component analysis (PCA) of soil enzyme activities over time. Aryl N: arylamidase; Aryl S: arylsulfatase, C: cellulase; FDAse: fluorescein diacetate hydrolase, b-Gal: b-galactosidase; b-Glu: b-glucosidase; PO: phenol oxidase; Pma: acid phophomonoesterase; Pmb: alkaline phosphomonoesterase; Pdi: phosphodiesterase; Ptri: phosphotriesterase. Error bars represent the standard error of mean of three replicates (n ¼ 3).

5 2 months

6 6 months

7

8

9

10

12 months

Fig. 6. Effect of pesticides on amines/amides, amino acids and carbohydrates used in BiologÒ Ecoplates at different incubation times. For treatments, see Table 1. Error bars represent the standard error of mean of three replicates (n ¼ 3). (*) Symbols indicate significant difference from control without pesticide addition for each incubation time (Tukey’s HSD test, P < 0.05).

C. Floch et al. / European Journal of Soil Biology 47 (2011) 256e263

Carboxilic acids AWCD 0.5

1

∗

0

-1

1

2

3

4

5

0 month

6

2 months

Miscellaneous AWCD 0.5

1

8

9

10

9

10

9

10

12 months

∗

0

-1

1

2

3

4 0 month

5

6

2 months

6 months

7

8

12 months

Polymers

1

AWCD 0.5

7

6 months

0

-1

1

2

3

4 0 month

5

6

2 months

6 months

7

8

12 months

Fig. 7. Effect of pesticides on carboxylic acids, miscellaneous and polymers used in BiologÒ Ecoplates at different incubation times. For treatments, see Table 1. Error bars represent the standard error of mean of three replicates (n ¼ 3). (*) Symbols indicate significant difference from control without pesticide addition for each incubation time (Tukey’s HSD test, P < 0.05).

groups of the proteins and consequently affect their catalytic activities. Thus, in our study, stimulating or inhibitory pesticide effects on some soil enzyme activities could be partly explained by such direct interaction. Pesticides may also indirectly affect soil enzyme activities through their action on soil microorganisms. Notably, numerous soil microorganisms, owing to their enzyme pools, are involved in the biodegradation of pesticides [7]. In a recent review paper, Singh and Walker [32] have identified a broad spectrum of microorganisms able to use organophosphorus compounds as sole source of carbon, nitrogen or phosphorus. These sources of available nutrients for microorganisms may consequently affect the biosynthesis mechanisms of enzymes by induction or repression phenomena. With regard to phosphatases, several studies have shown that both inorganic and organic phosphorus compounds strongly affect P mineralizing enzyme activities [11,29,33]. However, in our study, organophosphates (i.e. glyphosate, azinphos-methyl and parathion-

261

methyl) did not particularly affect soil phosphatase activities, since response patterns showed quite erratic fluctuations over time. Pesticides may also act on physiological processes of microorganisms, as reported by Cervelli et al. [10]. Hence, cell lyses or modifications of membrane excretory mechanisms subsequent to pesticide contamination contribute indirectly to shifts in soil enzyme activities. Such phenomena could explain the initial stimulating pesticide effects on some soil enzyme activity pools (e.g. b-glucosidase). Moreover, as hypothesized by Dick [13], after the initial stimulatory effect of a new substrate, production of high levels of enzymes can be inhibited by a feedback mechanism due to an adequate supply of energy and nutrient sources to microorganisms. All these characteristics of the interactions between soil microbiota and pesticides must in part explain the different effects on soil enzyme activities that we observed during our study. Finally, intrinsic properties of soil, such as pH, humus or clay content, can also strongly influence pesticide effects on soil enzyme activities [37]. Even though our study does not allow us to draw hard and fast conclusions on the influence of soil type on pesticide effects, it can be hypothesized that these intrinsic properties may also explain some pesticide effects. Indeed, while 2,4D is known to be toxic for numerous microorgansisms, our results showed that this pesticide is not the most effective in inhibiting soil enzymes. This could be explained by the alkalinity (pH 8.3) of the soil used, since, as mentioned by Welp and Brümmer [41], for soil pH higher than the 2,4D pK value (2.73), the resulting ionic form is less toxic than its non-ionic form. Moreover, these complex relationships between soil physico-chemical properties and pesticide effects on soil enzyme activities have been shown to vary from pesticide to pesticide. Gianfreda et al. [22], for example, reported positive and significant correlation between soil properties and soil urease activities following paraquat addition, whereas no such correlation was found with glyphosate. 4.2. Dynamics of soil enzyme activities and their potential as indicators of pesticide contamination Several previous studies [15,35] have shown that pesticide effects on soil enzyme activities vary with incubation time. The use of microcosms allowed us to avoid seasonal variations in soil enzyme activities, which could make interpretation of results and selection of bioindicators difficult under field conditions. Hence, this experimental design ensured that temporal responsiveness of soil enzyme activities recorded was due to pesticide effect alone. As a consequence and in the light of our results, we suggest that soil biological quality indexes including soil enzyme activities must also include an exposure time scale. Indeed, results showed that soil enzyme activities can be categorized in three groups according to their dynamics subsequent to pesticide addition, and thus to their potential as indicators of pesticide contamination.

Table 4 Results of one-way repeated measures ANOVA’s from microbial parameters. Symbols indicate significant differences from control without pesticide addition over time (Tukey’s HSD test. *: P < 0.05; **: P < 0.01; ***: P < 0.001). Bacterial functional diversity: substrate guild

Pesticide 1

2

3

4

5

6

7

8

9

10

Amines/amides Amino acids Carbohydrates Carboxylic acids Miscellaneous Polymers

ns ns ns ns ns 4.39*

5.88** ns ns ns ns ns

5.28** ns ns ns 3.14* ns

8.55*** ns ns ns ns 4.02*

10.42*** ns ns ns ns 4.19*

4.47** ns 2.90* ns ns ns

5.88** ns ns ns ns ns

3.69* ns ns ns ns 6.02**

3.01* ns ns ns ns 6.08**

ns 4.28* ns ns 3.38* ns

Pesticide score (%)

17

17

33

33

33

33

17

33

33

17

Substrate guild score (%) 80 10 10 0 20 50

Scores give the % of significant effects when considering “all pesticides vs substrate (substrate guild score)” or “each pesticide vs all substrates (pesticide score). For pesticide treatments, see Table 1.

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results showed no clear relationship between type of pesticide and the dynamics of this enzyme activity during incubation time, probably because of its own particular non-substrate specificity. Therefore, it can be concluded that these soil enzyme activities, which our study showed not to be sensitive to pesticides, cannot be considered useful indicators of soil pollution in such contamination contexts. However, we believe that field experiments are required to validate such observations, and we are currently performing such experiments in orchards with different agricultural practices.

3

0 month 2 months 6 months 12 months

PC2 (19.41%)

2

P

1

Aa A

0

4.3. Soil enzyme activities vs other microbial parameters

M -1

C Ca -2 -2

-1

0

1

2

3

4

PC1 (32.66%) Fig. 8. Principal component analysis (PCA) for BiologÒ Ecoplates over time. A: amines/ amides; Aa: amino acids; C: carbohydrates; Ca: carboxylic acids; M: miscellaneous; P: polymers. Error bars represent the standard error of mean of three replicates (n ¼ 3).

The 1st group includes only one enzyme, phenol oxidase. This enzyme behaved very differently from the others, being the only one in several cases to exhibit sudden and early (2 months) increases in activity, followed quickly by a decrease which resulted in all cases in a resilience status of this activity. Consequently, we hypothesize here that this enzyme can be used as an early indicator of pesticide contamination, since its enhanced activity was only detected at the beginning of the incubation and over a short period. Jaszek et al. [25] have recently pointed out that PO, such as laccases, could be involved in stress responses of certain microorganisms to chemical or environmental disturbances, allowing them to elimi nate some toxic forms of oxygen such as O2. Our results on PO induction in soil indicate the need to determine whether this induction is a stress response of soil microorganisms following pesticide application. Moreover, it could also be interesting to study PO dynamics over a shorter incubation time than 2 months, the minimum for assays in our study. The 2nd group includes arylamidase and b-glucosidase activities, which varied with incubation time and tended to return to their initial soil background levels after 12 months’ incubation. The recovery of these soil enzyme activities with time could be due to diminished effects of pesticides, either though degradation or though gradual adsorption on soil constituents. It could also be due to the adaptation of the microbial community to pesticides. Because of their regular trends and reproductive dynamics whatever the pesticide added, we suggest that such soil enzyme activities should be monitored to evaluate soil resilience after pesticide disturbance. Further studies could usefully aim to evaluate the appropriacy of these enzymes as indicators of soil resilience; it could be interesting to investigate the effect of repeated pesticide treatments on such enzymes, because soil resilience can be markedly different after a previous exposure [6]. The 3rd group includes all the other soil enzyme activities studied, which yielded less insight due to their fluctuations over time and, in some cases, their very low detection threshold (e.g. phosphotriesterase). As mentioned by Schloter et al. [31], “keystone” enzymes should not necessarily have a role in the assessment of soil quality. Several studies [4,23] suggest that fluorescein diacetate hydrolase can be used as an indicator of soil biological activity because FDA is a non-specific enzymatic substrate that can be hydrolyzed by a number of different extracellular and intracellular enzymes (e.g. esterases, proteases, lipases, cutinases). However, our

Substrate-utilization patterns are currently established via BiologÒ Ecoplates to determine changes in the functioning of soil microbial communities [5,19]. We determined bacterial functional diversity for each substrate guild in BiologÒ Ecoplates. PCA showed that all substrate guilds were highest for samples at 2 months’ incubation, probably indicating that bacterial communities are able to degrade complex substrates containing pesticides added to soil. However, other bacterial growth experiments using each pesticide as sole C source need to be performed before it can be concluded that the indigenous bacterial community has indeed become a degrading community. Unfortunately, substrate guilds such as pesticides do not currently exist in the BiologÒ system and could usefully be developed for further ecotoxicological studies. Moreover, for samples at 0, 6 and 12 months’ incubation pesticide addition had negligible effects on all the substrate guilds. This may be attributed to the resilience status of several soil functions after 6 months’ incubation. Results for both soil enzyme activities and functional diversity converged globally to indicate soil resilience trends after 12 months’ incubation, but a longer period would be needed for conclusive proof of patterns of soil biological function recovery. Finally, analyses of variance clearly showed that functional diversity of bacterial communities was a less sensitive tool to indicate pesticide contamination than soil enzyme activities. Therefore, soil enzyme activities may reveal more about soil microbial functions in such contaminated environments. 5. Conclusion Result of this study clearly showed that pesticide contamination effects can be better detected by using certain soil enzyme activities than by using the functional diversity of bacterial community via BiologÒ Ecoplates. Moreover, two types of indicators appropriate for different purposes were distinguished. On the one hand, phenol oxidase could be used as an early indicator of pesticide contamination; on the other hand, arylamidase and b-glucosidase activities could be monitored to evaluate soil resilience after pesticide disturbances. During the experimental approach, microcosms were particularly useful to investigate a wide range of pesticide effects on soil enzyme activities. However, numerous factors encountered in the natural environment were not included; moreover, soils are generally subject to multiple pesticide contaminations instead of a single contamination. It can be also assumed that commercial formulations with additives other than pesticides will have different effects on soil microbial functions than pure active ingredients. Hence, it would be desirable in further studies to corroborate our results under field conditions in agroecosystems with phytosanitary treatments including pesticides. Acknowledgments Financial support was provided by the French Agency for the Environment and Energy Management (ADEME) and the French Agency for Water in the Rhône-Méditerranée-Corse area (Agence

C. Floch et al. / European Journal of Soil Biology 47 (2011) 256e263

de l’eau RMC). We greatly thank Mr. Antonio BISPO (ADEME) and Mrs. Lysanne BOUR (Agence de l’eau RMC). We would especially like to acknowledge Mrs. Marjorie SWEETKO for improving the English of the manuscript.

References [1] V. Acosta-Martinez, M.A. Tabatabai, Arylamidase activity of soils, Soil Sci. Soc. Am. J. 64 (2000) 215e221. [2] Agence de l’eau RMC, Qualité des eaux superficielles et souterraines en Rhône Méditerranée (2008) pp. 21. [3] E. Alarcon-Gutiérrez, C. Floch, F. Ruaudel, S. Criquet, Non-enzymatic hydrolysis of fluorescein diacetate (FDA) in a Mediterranean oak (Quercus ilex L.) litter, Eur. J. Soil Sci. 59 (2008) 139e146. [4] A.K. Bandick, R.P. Dick, Field management effects on soil enzyme activities, Soil Biol. Biochem. 31 (1999) 1471e1479. [5] G.D. Bending, C. Putland, F. Rayns, Changes in microbial community metabolism and labile organic matter fractions as early indicators of the impact of management on soil biological quality, Biol. Fertil. Soils 31 (2000) 78e84. [6] E. Benitez, R. Melgar, R. Nogales, Estimating soil resilience to a toxic organic waste by measuring enzyme activities, Soil Biol. Biochem. 36 (2004) 1615e1623. [7] J.M. Bollag, S.Y. Liu, Biological transformation processes of pesticides. in: H.H. Cheng (Ed.), Pesticide in the Soil Environment: Processes, Impacts, and Modelling. Soil Science Society of America, Madison, 1990, pp. 169e211. [8] L.A. Burrows, C.A. Edwards, The use of integrated soil microcosms to predict effects of pesticides on soil, Eur. J. Soil Biol. 38 (2002) 245e249. [9] R. Calbrix, K. Laval, S. Barray, Analysis of the potential functional diversity of the bacterial community in soil: a reproducible procedure using sole-carbonsource utilization profiles, Eur. J. Soil Biol. 41 (2005) 11e20. [10] S. Cervelli, P. Nannipieri, P. Sequi, Interactions between agrochemicals and soil enzymes. in: R.G. Burns (Ed.), Soil Enzymes. Academic Press Inc, London, U.K., 1978, pp. 251e280. [11] S. Criquet, A. Braud, Effects of organic and mineral amendments on available P and phosphatase activities in a degraded Mediterranean soil under short-term incubation experiment, Soil Till. Res. 98 (2008) 164e174. [12] S.P. Deng, M.A. Tabatabai, Cellulase activity of soils, Soil Biol. Biochem. 26 (1994) 1347e1354. [13] R.P. Dick, Soil enzyme activities as indicators of soil quality. in: Doran, et al. (Eds.), Defining Soil Quality for a Sustainable Environment. Soil Science Society of America, Madison, 1994, pp. 107e124. [14] Y.J. Dong, M. Bartlam, L. Sun, Y.F. Zhou, Z.P. Zhang, C.G. Zhang, Z. Rao, X.E. Zhang, Crystal structure of methyl parathion hydrolase from Pseudomonas sp. WBC-3, J. Mol. Biol. 353 (2005) 655e663. [15] C.A. Edwards, Assessing the effects of environmental pollutants on soil organisms, communities, processes and ecosystems, Eur. J. Soil Biol. 38 (2002) 225e231. [16] F. Eivazi, M.A. Tabatabai, Phosphatases in soils, Soil Biol. Biochem. 9 (1977) 167e172. [17] F. Eivazi, M.A. Tabatabai, Glucosidases and galactosidases in soils, Soil Biol. Biochem. 20 (1988) 601e606. [18] C. Floch, E. Alarcon-Gutiérrez, S. Criquet, ABTS assay of phenol oxidase activity in soil, J. Microbiol. Methods 71 (2007) 319e324. [19] J.L. Garland, A.L. Mills, Classification and characterization of heterotrophic microbial communities on the basis of patterns of community-level solecarbon-source utilization, Appl. Environ. Microbiol. 57 (1991) 2351e2359. [20] B. Gevao, K.T. Semple, K.C. Jones, Bound pesticide residues in soils: a review, Environ. Pollut. 108 (2000) 3e14.

263

[21] L. Gianfreda, F. Sannino, M.T. Filazzola, A. Violante, Influence of pesticides on the activity and kinetics of invertase, urease and acid-phosphatase enzymes, Pestic. Sci. 39 (1993) 237e244. [22] L. Gianfreda, F. Sannino, A. Violante, Pesticide effects on the activity of free, immobilized and soil invertase, Soil Biol. Biochem. 27 (1995) 1201e1208. [23] V.S. Green, D.E. Stott, M. Diack, Assay for fluorescein diacetate hydrolytic activity: optimization for soil samples, Soil Biol. Biochem. 38 (2006) 693e701. [24] D. Hernández-Rodríguez, J.E. Sánchez, M.G. Nieto, F.J. Márquez-Rocha, Degradation of endosulfan during substrate preparation and cultivation of Pleurotus pulmonarius, World J. Microbiol. Biotechnol. 22 (2006) 753e760. [25] M. Jaszek, J. Zuchowski, E. Dajczak, K. Cimek, M. Graz, K. Grzywnowicz, Ligninolytic enzymes can participate in a multiple response system to oxidative stress in white-rot basidiomycetes: Fomes fomentarius and Tyromyces pubescens, Int. Biodeterior. Biodegrad. 58 (2006) 168e175. [26] J. Preston-Malfham, L. Boddy, P.F. Randerson, Analysis of microbial functional diversity using sole-carbon-source utilization profiles e a critique, FEMS Microbiol. Ecol. 42 (2002) 1e14. [27] X.H. Qiu, W.Q. Bai, Q.Z. Zhong, M. Li, F.Q. He, B.T. Li, Isolation and characterization of a bacterial strain of the genus Ochrobactrum with methyl parathion mineralizing activity, J. Appl. Microbiol. 101 (2006) 986e994. [28] S. Rønhede, B. Sebastian, R. Sørensen, B. Jensen, J. Aamand, Mineralization of hydroxylated isoproturon metabolites produced by fungi, Soil Biol. Biochem. 39 (2007) 1751e1758. [29] F. Sannino, L. Gianfreda, Pesticide influence on soil enzymatic activities, Chemosphere 45 (2001) 417e425. [30] M. Schiavon, C. Perringanier, J.M. Portal, The pollution of water by pesticides e state and origin, Agronomie 15 (1995) 157e170. [31] M. Schloter, O. Dilly, J.C. Munch, Indicators for evaluating soil quality, Agric. Ecosyst. Environ. 98 (2003) 255e262. [32] B.K. Singh, A. Walker, Microbial degradation of organophosphorus compounds, FEMS Microbiol. Rev. 30 (2006) 428e471. [33] T.W. Speir, D.F. Ross, Soil phosphatase and sulphatases. in: R.G. Burns (Ed.), Soil Enzymes. Academic Press Inc, London, U.K., 1978, pp. 197e250. [34] M.T. Strandberg, J.J. Scott-Fordsmand, Field effects of simazine at lower trophic levels e a review, Sci. Total Environ. 296 (2002) 117e137. [35] P. Sukul, Enzymatic activities and microbial biomass in soil as influenced by metalaxyl residues, Soil Biol. Biochem. 38 (2006) 320e326. [36] M.A. Tabatabai, J.A. Bremmer, Use of p-nitrophenylphosphate for assay of soil phosphatase activity, Soil Biol. Biochem. 1 (1969) 301e307. [37] M.A. Tabatabai, Soil enzymes. in: W.A. Dick (Ed.), Methods of Soil Analysis, 2. Microbiological and Biochemical Properties. Soil Science Society of America, Madison, 1994, pp. 775e833. [38] M.A. Tabatabai, J.M. Bremmer, Arylsulfatase of soils, Soil Sci. Soc. Am. J. 34 (1970) 225e229. [39] L. Vieublé Gonod, F. Martin-Laurent, C. Chenu, 2,4-D impact on bacterial communities, and the activity and genetic potential of 2,4-D degrading communities in soil, FEMS Microbiol. Ecol. 58 (2006) 529e537. [40] C. Viti, A. Mini, G. Ranalli, G. Lustrato, L. Giovannetti, Response of microbial communities to different doses of chromate in soil microcosms, Appl. Soil Ecol. 34 (2006) 125e139. [41] G. Welp, G.W. Brümmer, Effects of organic pollutants on soil microbial activity: the influence of sorption, solubility, and speciation, Ecotoxicol. Environ. Saf. 43 (1999) 83e90. [42] X.H. Yao, H. Min, Z.L. Lu, H.P. Yuan, Influence of acetamiprid on soil enzymatic activities and respiration, Eur. J. Soil Biol. 42 (2006) 120e126.