Effects of cattle-lagoon slurry on a soil microbial community can be observed until depths of 50 m

Applied Soil Ecology 49 (2011) 32–39

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Effects of cattle-lagoon slurry on a soil microbial community can be observed until depths of 50 m Galit Hermann a , Laurence S. Shore b , Yosef Steinberger a,∗ a b

The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel Kimron Veterinary Institute, P.O. Box 12, Bet Dagan 50250, Israel

a r t i c l e

i n f o

Article history: Received 20 January 2011 Received in revised form 19 June 2011 Accepted 7 July 2011 Keywords: Soil microbial community Cattle slurry Lagoon Microbial community vertical distribution Microbial biomass Microbial functional diversity

a b s t r a c t The large amount of effluent generated by concentrated animal feeding operations (CAFOs) has raised concerns about contamination of groundwater and pollution of streams by compounds that penetrate the vadose zone. However, the possibility that a microbial community in the vadose zone under cattleslurry lagoons (CSLs) may also be affected has not been considered. In the present study, we investigated the influence of long-term (30 years) accumulation of cattle slurry on the vertical distribution of a soil microbial community (microbial biomass [MB], CO2 evolution, substrate utilization ability), until a 50-m depth, compared to a control site. Total soluble nitrogen (TSN) was found to be elevated fourfold, and MB was found to be threefold higher under the CSL compared to a control site. In general, the increase in MB is associated with higher soil moisture and higher nitrogen content. Substrate utilization ability was found to be significantly higher in a CSL in comparison to the control site. At the CSL site, a higher utilization of aromatic carboxylic acids typical of cattle slurry was obtained in the deeper soil layers (7–30 m), indicating a degree of microbial adaptation even at these depths. The soil layers under the CSL were more dynamic as the microbial functional diversity was significantly different between the layers, while no such difference was seen at the reference site. Our results, therefore, suggest that the infiltration of cattle slurry can affect the microbial community throughout the vadose zone. We also suggest that activity of the microbial community, as characterized by its substrate utilization ability, can be a bioindicator for anthropogenic activities and environmental changes even at depths below the rhizosphere (30 cm). © 2011 Elsevier B.V. All rights reserved.

1. Introduction Organic manure is an inevitable waste product of animals and is produced in enormous amounts in concentrated animal feeding operations (CAFOs) such as dairy, swine, and poultry farms (Lee et al., 2007). In sustainable agricultural management, animal waste is spread on agricultural fields as an organic fertilizer, improving nutrient availability via decomposition processes (Jedidi et al., 2004; Shore and Pruden, 2009). This decomposition and recycling of organic matter is largely due to soil microorganisms that are capable of converting the organic components into nutrients available to plants (Steinberger and Shore, 2009). The soil microbial community can also be used as bioindicators for detecting environ˜ mental and human impacts on soil quality (Rodríguez-Anón et al., 2007) such as CO2 enrichment, using PLFA and DNA fingerprint (DGGE) techniques at rhizosphere level (0–10 cm) (Ebersberger

∗ Corresponding author. Tel.: +972 3 5318571; fax: +972 3 7384058. E-mail address: [email protected] (Y. Steinberger). 0929-1393/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2011.07.004

et al., 2004) or by substrate utilization of a soil microbial community. Rillig et al. (1997) found that microbial communities associated with Gutierrezia sarothrae roots had different substrate utilization in response to CO2 enrichment, which indicated rhizodeposition. Moreover, the microbial community is a tool for measuring environmental cattle- and sheep-grazing effects (Kohler et al., 2005), such as trampling, herbage removal, and dunging. In particular, cattle activity in successive years may modify the potential metabolic activity of certain microbial guilds (Kohler et al., 2005), thus inducing changes in microbial-community structure. Similarly, Williams et al. (2000) found that the addition of synthetic sheep urine to upland grassland resulted in a dramatic and short-term change in soil microbial-community structure and activity. The objective of the present study was to explore the effect of a cattle-slurry lagoon of dairy-farm origin on the vertical distribution of a soil microbial community. In the site studied, untreated slurry accumulated in the lagoon for thirty years and the slurry infiltrated to deeper soil layers, causing changes in soil physical and chemical parameters that have already been described (Arnon et al., 2008).

G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39

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Table 1 Soil characteristics along the vertical profile beneath a cattle-slurry lagoon (CSL) and control sites. Soil type/location

Clay (vertisols)

Sandy loam

Calcic sand

Brown–red sandy soils (podsoils)

Calcic sand with pebbles

CSL Control

0–6 m 0–10 m

6–8 m 10–15 m

8–50 m 15–25 m

– 25–40 m

– 40–50 m

Table 2 Soil layers of the vertical profile beneath a cattle-slurry lagoon (CSL) and control sites. Soil layer

CSL (m)

Control (m)

I II III IV V VI

0.15, 0.5, 0.85 1, 2, 4, 5 6, 7, 8, 9, 12, 15 19, 25, 30 35, 40, 45 50

0.15, 0.5 1, 2, 4 7, 10, 15 20, 25, 30 40, 45 50

2.1.1. Soil moisture SM was expressed as a percentage determined gravimetrically by drying 5 g soil samples for 72 h at 105 ◦ C. 2.1.2. Organic matter OM was expressed as a percentage determined by oxidation with 1 N potassium dichromate in acidic medium, according to Rowell (1994).

2. Materials and methods

2.1.3. Total soluble nitrogen TSN was measured by the extraction of 10 g soil samples in 25 ml 0.01 M CaCl2 , and determined with a Skalar Autoanalyzer (Houba et al., 1987; S.F.A.S., 1995).

2.1. Study site

2.2. Soil microbial community

A 30-year-old dairy farm located in the south-east section of the Israeli aquifer, with a semi-arid climate and 300 mm multi-annual precipitation, was used in the present study (Shahar, 2009). The dairy farm included 60 dairy cows and ∼30 calves. The output of effluent solid matter per day was 7 kg/cow, resulting in 70 kg of effluent/day per cow, of which 10% was solid matter. The facility used was a 150 m2 single-stage earthen unlined waste lagoon with an average depth of 0.5 m, which is common manure-management practice in the area. Excess wastewater overflowed directly into a dry creek, without any particular maintenance procedures such as drainage or removal of solids. A continuous slurry flow into a nearby creek over a period of 30 years created a slurry lagoon. Boreholes were mechanically drilled to a depth of 50 m in order to collect vertical sediment samples. One borehole was drilled under the cattle slurry lagoon (CSL) in summer, while a second borehole used as a control was drilled ∼1 km east of the dairy farm in a typical, open agricultural field (Arnon et al., 2008). The boreholes were entirely cased with PVC pipes and perforated from ∼1 m above the groundwater surface to the bottom of the borehole, which was ∼7 m below groundwater level (groundwater levels were 47 and 42 m below ground surface for CSL and control, respectively). In order to explore the vertical distribution of the soil microbial community, we used a dry-drilling method with a bucket auger. The bucket was cleaned between samples with pressurized water and a propane flame to prevent cross-contamination. Soil samples were taken from the soil surface to a 50-m-depth, with denser sampling at the top of the profile (20 samples under CSL and 14 samples under the control site; n = 3). Each soil sample was placed in an individual plastic bag that was placed in a cooler to prevent heating, and transported within 3 h to the lab, where they were kept at 4 ◦ C till chemical and biological analyses were performed. The soil sediment properties at the study site were determined by Arnon et al. (2008). Along the vertical gradient, three types of sediment were found: clay mineral was found at the upper layer, followed by a transition layer of sandy-loam, and to a sand-calcareous layer. This is typical of the brown–red sandy soil of the Israeli coastal plain (Holocene-Upper Pleistocene), with a 50–60% clay fraction toward the deeper layers (Gal et al., 1974; Fitzpatrick, 1996) (Table 1). The soil pH was 8.17 ± 0.13 and 8.23 ± 0.08 for the CSL and control sites, respectively. Soil samples collected from each plot were divided, according to Ravikovitch (1981), into six compatible soil layers based on similarities in chemical, physical, and biological components (Table 2).

The soil microbial community was determined by the MicroRespTM method (Campbell et al., 2003), with which we assessed the community level physiological profile (CLPP), microbial biomass (MB), and CO2 evolution. This method is based on determining the potential utilization of 15 different carbon sources that are typical of the utilization of carbohydrates (Carb), carboxylic acids (CA), amino acids (AA), and aromatic carboxylic acids (ACA) by the soil microbial community (Campbell et al., 2003; Berg and Steinberger, 2008; Saul-Tcherkas and Steinberger, 2009). In order to determine microbial biomass (MB), glucose solution was added to soil samples, while no substrates were added to samples in order to determine basal CO2 evolution (Anderson and Domsch, 1978; Carpenter-Boggs et al., 2000; Berg and Steinberger, 2010). The dye plates were read twice in a spectrophotometer at 590 nm: just before they were placed on the deep plates containing the soil samples (Time 0) and after discerning colorimetric changes in the indicator plate (Time 1). After Time 0, the plates were incubated in the dark at 27 ◦ C. The results per well were calculated in comparison to the 16th well that contained the same soil sample. Microbial functional diversity was determined using the Shannon–Weaver index (H  ) : H  −



Pi (ln Pi ),

where Pi is the ratio of the activity of a particular substrate and the sum of activities of all substrates (Zak et al., 1994). 2.3. Statistical analysis All the data obtained in the present study were subjected to statistical analysis of variance (ANOVA) using the SAS model (Duncan’s multiple range test and Pearson correlation coefficient [SAS Institute, Inc.], one-way ANOVA, and T test) for evaluating differences between separate means. Differences at the p < 0.05 level were considered significant (n = 3) (Kandeler et al., 1999). 3. Results 3.1. Soil moisture (SM) The vertical distributions of soil moisture (SM) percentage expressed as mean values of samples collected along the 50 m from the cattle-slurry lagoon (CSL) (12.2%) and the control site (12.9%),

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G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39

Table 3 Univariate analysis of variance (ANOVA) for the effect of sampling site, soil layer, and the interaction between them, correlated with different soil variables. Variables

Sampling site

Soil layer

Sampling site * Soil layer

SM OM TSN CO2 evolution MB H AA ACA Carb CA CLPP

NS NS <0.0001 NS 0.001 NS NS 0.0197 NS NS 0.043

<0.0001 <0.0001 <0.0001 0.05 <0.0001 0.014 NS NS NS 0.0375 0.04

<0.0001 0.0013 0.0077 NS <0.0001 NS NS NS NS NS NS

was found to be highly similar, although a significant difference (p < 0.05) between the two was obtained in deeper soil layers such as III, V, and VI (Fig. 1A).

3.2. Organic matter (OM)

Soil moisture (SM), organic matter (OM), total soluble nitrogen (TSN), CO2 evolution, microbial biomass (MB), Shannon index (H ), and microorganism utilization ability of amino acids (AA), aromatic carboxylic acids (ACA), carbohydrates (Carb), carboxylic acids (CA), community level physiological profile (CLPP). NS, not significant (p > 0.05).

were not significantly different. Despite this, SM percentage was found to be significantly (p < 0.0001) affected and negatively correlated with the soil layer in the CSL and control site (−0.58 and −0.59, respectively) (Tables 3 and 4). Moreover, SM was significantly (p < 0.0001) influenced by the interaction between sampling site and soil layer. SM along the six layers obtained from the CSL site showed a significant (p < 0.05) reduction from 24.7% in the upper layer I to a level of 4.21% in the fifth (V) layer, while at the deepest layer (VI), an almost five-fold increase occurred to a level of 19.06% (Fig. 1A; Table 5). A similar pattern was observed in the samples collected from the control site, where soil layer I (one) was found to be significantly (p < 0.05) higher (22.41%) in comparison to the deeper soil layers III, IV, V, and VI (14.35, 3.91, 9.53, and 10.4%, respectively). The trend in the soil moisture between the two sites

A vertical profile of the OM percentage reveals significant differences (p < 0.05) between the CSL and control site (Fig. 1B). At soil layer II, the OM percentage was found to be four times (p < 0.05) higher in the control site (15.37%) compared to the CSL site (4.25%), a trend that was reversed in deeper soil layers (III and IV), where significantly (p < 0.05) higher OM values were observed in the CSL than in the control site (4.22 vs. 6.13% and 1.86 vs. 1.51% for layers III and IV). These relatively higher values in the CSL compared to the control site were also observed in the two sequential soil layers, V and VI (3.07 and 3% in the CSL vs. 0.25 and 0.1 the control, however, this did not reach statistical significance). Likewise, the OM values were found to be significantly (p < 0.0001) affected by soil layer and by the combination of soil layer and sampling site (p < 0.0013) (Table 3; Fig. 1B). The OM percentage in the soil samples collected from the CSL along the six (I–VI) layers to a depth of 50 m was found to range between 3 and 9.88%, with significant (p < 0.05) differences between the soil layers (Table 5). In the upper soil layer (I), OM percentage (9.88%) was significantly higher (p < 0.05) than soil layers II, III, V, and VI (6.72, 2.92, 3.06, and 3.0%, respectively). The OM percentage in soil layer IV was not significantly different from the above (I, II, III) soil layers and was detected as 6.13%. In addition, significant (p < 0.05) differences in OM values were found in the control site between soil layers (Table 6). In soil layers I and II, significantly (p < 0.05) higher OM percentages, 17.13 and 15.361%, respectively, were found compared to those detected in the deeper soil layers III, IV, V, and VI (1.85, 1.51, 0.25, and 0.1%, respectively). There was a significantly (p < 0.0001) negative correlation (−0.62)

Table 4 Correlation coefficient for soil samples collected from the cattle slurry lagoon (CSL) and control sites. Variable

SM TSN OM CO2 evolution MB H

Soil layer

OM

TSN

MB

CSL

Control

Control

CSL

Control

CSL

Control

−0.58*** −0.51** NS 0.31* −0.64*** NS

−0.52*** −0.51* −0.62*** NS NS NS

0.44** NS NS NS NS NS

0.64*** NS NS NS 0.69*** NS

0.57** NS 0.75*** NS NS NS

0.66*** 0.69*** NS NS 1 0.33**

NS NS NS NS 1 0.37*

Soil moisture (SM), total soluble nitrogen (TSN), organic matter (OM), CO2 evolution, microbial biomass (MB) and H (Shannon index). NS, not significant (p > 0.05). * p < 0.05. ** p < 0.01. *** p < 0.0001. Table 5 Mean values of different parameters in soil samples collected from cattle slurry lagoon (CSL) site. Soil layer

I

II

III

IV

V

VI

SM (%) OM (%) TSN (mg kg soil−1 ) CO2 evolution (␮gCO2 -C g soil−1 h−1 ) MB (␮gCO2 -C g soil−1 ) H (␮gCO2 -C g soil−1 h−1 ) AA (␮gCO2 -C g soil−1 h−1 ) ACA (␮gCO2 -C g soil−1 h−1 ) Carb (␮gCO2 -C g soil−1 h−1 ) CA (␮gCO2 -C g soil−1 h−1 ) CLPP (␮gCO2 -C g soil−1 h−1 )

24.7a 9.8a 11.97a 0.41b 99.5a 2.0a 2.2ab 1.2b 0.54ab 11.4ab 15.45ab

23.3ab 4.2b 6.72b 0.35b 136.4a 1.8a 4.7ab 2.7ab 3.10ab 10.23ab 20.86ab

4.5c 4.2b 2.92b 0.03b 16.32b 1.7ab 0.4ab 3.5ab 0.05b 12.21ab 16.25ab

3.8c 6.1ab 3.58b 2.92ab 30.5b 1.6ab 13.9a 7.8a 6.75a 23.04ab 51.54a

4.2c 3.0b 3.50b 3.57a 1.0b 1.9a 13.0ab 4.0ab 4.80ab 31.48a 53.3a

19.0b 3.0b 2.70b 0b 1.2b 1.5b 0b 0.4b 0b 0.47b 0.88b

Soil moisture (SM), organic matter (OM), total soluble nitrogen (TSN), CO2 evolution, microbial biomass (MB), Shannon index (H ), and microorganism utilization ability of amino acids (AA), aromatic carboxylic acids (ACA), carbohydrates (Carb), carboxylic acids (CA), and community level physiological profile (CLPP). Different letters indicate significant differences between soil layers (p < 0.05).

G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39

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Table 6 Mean values of different parameters in soil samples collected from control site. Soil layer

I

II

III

IV

V

VI

SM (%) OM (%) TSN (mg kg soil−1 ) CO2 evolution (␮gCO2 -C g soil−1 h−1 ) MB (␮gCO2 -C g soil−1 ) H AA (␮gCO2 -C g soil−1 h−1 ) ACA (␮gCO2 -C g soil−1 h−1 ) Carb (␮gCO2 -C g soil−1 h−1 ) CA (␮gCO2 -C g soil−1 h−1 ) CLPP (␮gCO2 -C g soil−1 h−1 )

22.4 a 17.1 a 2.95 a 0.56 ab 10.1 a 1.8 a 1.2 b 1.0 a 0.77 b 4.55 b 7.69b

17.5 ab 15.3 a 0.80 b 0.18 b 20.1 a 1.7 a 1.7 ab 1.3 a 0.51 b 6.01 b 9.64b

14.3 bc 1.8 b 0.86 b 0.18 b 28.6 a 1.0 a 0.3 b 0.4 a 0.24 b 1.28 b 2.32b

3.9 d 1.5 b 0.61 b 0.10 b 20.4 a 1.9 a 0.2 b 0a 0.30 b 0b 0.53b

9.5 cd 0.2 b 0.55 b 1.02 a 8.5 a 1.7 a 5.4 a 2.1 a 2.32 ab 26.70 a 36.63a

10.4 cd 0.1 b 0.50 b 0.50 ab 5.1 a 1.6 a 1.2 b 0.3 a 3.10 a 14.05 ab 18.66ab

Soil moisture (SM), organic matter (OM), total soluble nitrogen (TSN), CO2 evolution, microbial biomass (MB), Shannon index (H ), and microorganism utilization ability of amino acids (AA), aromatic carboxylic acids (ACA), carbohydrates (Carb), carboxylic acids (CA), and community level physiological profile (CLPP). Different letters indicate significant differences between soil layers (p < 0.05).

Soil Moisture (%) 0

5

10

15

0

I

5 b

III

25

30

0

a

a

a

II

10

TSN (mg*kg soil-1)

20

a

Depth (m)

a

Soil layer

Depth (m)

a

IV

30 35

15 a

a

II a

III

20 25

b

a

IV

b

a

V

30 35

b

40

V

a

40

CSL

45

45 b

50

VI

0

5

0

b

10 I

50

5

II

10

a

b

15 a

20 a

a

a IV

30 35 a

a

a

a

a

VI

Control

Fig. 2. Changes in mean values of TSN along a vertical profile in soil from a cattleslurry lagoon (CSL) and control site. Parallel soil layers marked with different letters indicate significant differences (p < 0.05).

3.3. Total soluble nitrogen (TSN)

20 b

b

III

15

25

CSL

Control

a

Organic Matter (%)

Depth (m)

I

b

b

10

15

25

V

45 50

b

10

a

20

40

5

5

15

B

0

Soil layer

A

CSL

VI

Control

Fig. 1. Changes in mean values of soil moisture (%) (A) and soil organic matter (%) (B) along a vertical profile from a cattle-slurry lagoon (CSL) and control site. Parallel soil layers marked with different letters indicate significant differences (p < 0.05).

between OM values and soil layer in the control site, as well as a significantly (p < 0.01) positive correlation (0.44) between OM values and SM values (Table 4).

All data obtained on total soluble nitrogen (TSN) were found to show similar trends for the CSL as well as for the control sampling sites, with significant (p < 0.0001) differences between the two (Fig. 2; Table 3). In the CSL, the mean TSN value was found to be five-fold higher (5.0571 mg kg soil−1 ) in comparison to the control site, with a value of 1.02 mg kg soil−1 . Furthermore, TSN values were found to be significantly (p < 0.01, p < 0.05) affected and negatively correlated (−0.51) with the soil layers in the CSL and control site, respectively (Table 4). Accordingly, in the upper soil layer (I) in the CSL, a significantly (p < 0.05) higher TSN value of 11.97 mg kg soil−1 was measured compared to the remaining soil layers II, III, IV, V, and VI (6.72, 2.92, 3.58, 3.50 and 2.7 mg kg soil−1 , respectively) (Table 5). Regarding the control site, significant (p < 0.05) differences in TSN values were obtained between soil layers. In the upper soil layer (I), a significantly (p < 0.05) higher TSN value of 2.95 was measured compared to those in the remaining soil layers II, III, IV, V, and VI, with values of 0.8, 0.86, 0.61, 0.55, and 0.50 mg kg soil−1 , respectively (Table 6). Mean values of TSN were found to be strongly affected (p < 0.0077) by the combination of sampling site and soil layer (Table 3). The TSN values detected in soil beneath the CSL were constantly significantly (p < 0.05) higher in all parallel soil layers than those detected at the control site (Fig. 2A). Signifi-

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G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39

CO2 evolution (µg CO2-C*g soil-1* h-1) 0

1

a

a

a

5

a

3

4

I II

10

Depth (m)

2

a

b

III

3.5. Microbial biomass (MB)

20

MB distribution along the vertical profile underlined significant differences (p < 0.05) between the cattle-slurry lagoon (CSL) and the control site (Fig. 3B). In comparing between the soil layers at the two vertical samplings (soil layers I and II), the MB levels were significantly (p < 0.05) higher in the CSL compared to the control site, with mean values of 99.5 and 136.4 ␮gCO2 -C g dry soil−1 vs. 10.1 and 20.16 ␮gCO2 -C g dry soil−1 , respectively. Subsequently, in the deeper soil layers (III and IV), no significant differences between the CSL (16.32 and 30.5 ␮gCO2 -C g dry soil−1 , respectively) and control site (28.6 and 20.4 ␮gCO2 -C g dry soil−1 , respectively) were found. However, at the deeper soil layers (V and VI), the MB levels were found to show significantly (p < 0.05) higher values at the control site compared to the CSL site, with mean values of 8.5 and 5.1 ␮gCO2 -C g dry soil−1 vs. 1.0 and 1.2 ␮gCO2 C g dry soil−1 , respectively. Moreover, combining MB values of all soil layers (I–VI) between the CSL and control site demonstrated a significant (p < 0.05) difference between them. At the CSL site, the mean MB level was 62.78 ␮gCO2 -C g dry soil−1 , while at the control site, it was 18.42 ␮gCO2 -C g dry soil−1 . MB was found to be significantly (p < 0.0001) influenced by sampling site, soil layer, and the combination of them (p < 0.001) (Table 3). In CSL, the MB values were significantly (p < 0.05) different between soil layers (Table 5). In general, MB values at the CSL were three-fold higher than MB at the control site (62.7 vs. 18.4 ␮gCO2 -C g dry soil−1 ). Moreover, MB at the CSL site was found to be significantly (p < 0.0001) and negatively (r2 = −0.64) correlated with the soil layer, but positively correlated with TSN (p < 0.0001, r2 = 0.69), SM (p < 0.0001, r2 =0.66), and H p < 0.01, r2 =0.33) values (Tables 4 and 7).

25

a

IV

30

a

35 40

a

a

V

45

CSL

a 50

B

a

Control

VI

Microbial biomass (ug CO2-C*g soil-1) 0

0

50 b

I

b

5

100 a

150 a

II

10

a

a

III

20 a

25

a

IV

30

Soil layer

15

Depth (m)

and 0.50 ␮gCO2 -C g dry soil−1 h−1 , respectively) compared to the above-mentioned soil layers (Table 6). Parallel soil layers between the CSL and control sites (Fig. 3A) revealed a significant difference in soil layer III, in which the CO2 evolution value was significantly (p < 0.05) higher at the control site.

15

Soil layer

A

0

35 40 45 50

b b

a

a

V CSL Control

Fig. 3. Changes in CO2 evolution (A) and in mean values of microbial biomass (B) along a vertical profile from a cattle-slurry lagoon (CSL) and control site. Parallel soil layers marked with different letters indicate significant differences (p < 0.05).

cant (p < 0.0001) correlations (0.64) were found between SM and TSN values in the CSL as well as the control site, with a significant (p < 0.01) correlation of r2 = 0.57. A significant (p < 0.0001) correlation (r2 = 0.75) was found at the control site between TSN and OM values (Table 4). 3.4. CO2 evolution CO2 evolution was found to be significantly influenced and correlated (p = 0.05) with the soil layer (Table 3). It was found to fluctuate along the soil layers in the CSL, showing significantly (p < 0.05) lower values of 0.41, 0.35, and 0.03 ␮gCO2 -C g dry soil−1 h−1 in the upper three layers, respectively, in comparison to the deeper soil layer (V), with a 10-fold higher value (3.57 ␮gCO2 C g dry soil−1 h−1 ) (Fig. 3A). At soil layer VI, no CO2 evolution activity was detected (Table 5). Soil samples collected from the control site showed a different pattern in CO2 evolution rate along the vertical profile. The intermediate soil layers (II, III, IV), had significantly (p < 0.05) lower values (0.18, 0.18, and 0.10 ␮gCO2 -C g dry soil−1 h−1 , respectively), compared to the deeper soil layer V (1.02 ␮gCO2 -C g dry soil−1 h−1 ). Furthermore, the upper and deepest soil layers (I, VI) had in-between CO2 evolution values (0.56

3.6. Community-level physiological profile (CLPP) Significant (p < 0.05) differences were observed in the utilization ability of the microbial community between the CSL (26.42 ␮gCO2 C g dry soil−1 h−1 ) and control site (10.79 ␮gCO2 -C g dry soil−1 h−1 ). In the CSL, a significantly (p < 0.05) higher utilization of aromatic carboxylic acids (ACA) was observed, with values of 3.4 ␮gCO2 C g dry soil−1 h−1 , compared to the control site, with values of 0.8 ␮gCO2 -C g dry soil−1 h−1 . Prominent and significant (p < 0.05) differences in CLPP between the CSL and control sites were obtained in the III and IV parallel soil layers, with values of 16.24 and 51.54 ␮gCO2 -C g dry soil−1 h−1 and 2.31 and 0.53, ␮gCO2 -C g dry soil−1 h−1 , respectively (Fig. 4A and B). Regarding carbon-group utilization, the microbial community at the CSL site showed a significantly (p < 0.05) greater ability to utilize CA (12.2 ␮gCO2 -C g dry soil−1 h−1 ) in the intermediate soil layer III compared to the control site (1.28 ␮gCO2 -C g dry soil−1 h−1 ). In the subsequent soil layer IV, the differences were greater and in addition to CA, measured as 23.0 and 0 ␮gCO2 -C g dry soil−1 h−1 for the CSL and control site, respectively, significantly (p < 0.05) higher ACA utilization was detected in the CSL microbial community (7.84 ␮gCO2 -C g dry soil−1 h−1 ) compared to the control-site community (0 ␮gCO2 -C g dry soil−1 h−1 ). Substrate consumption measured along the vertical profile in the CSL showed different physiological behaviors of the microbial community. Soil layer IV exhibited significantly (p < 0.05) higher utilization of amino acids, ACA, and carbohydrates (13.9, 7.8, and 6.75 ␮gCO2 C g dry soil−1 h−1 , respectively) compared to soil layer VI (0, 0.4,

G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39

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Table 7 Correlation coefficient for soil samples collected from cattle slurry lagoon (CSL) and control sites. CO2 evolution

SM TSN CO2 evolution MB CA Carb ACA AA CLPP

H

MB

qCO2

CSL

Control

CSL

Control

CSL

Control

CSL

Control

0.66*** NS 1 NS 0.63*** 0.92*** 0.51*** 0.91*** 0.79***

NS NS 1 NS 0.86*** 0.77*** 0.46** 0.79*** 0.87***

NS 0.69*** NS 1 NS NS NS NS NS

NS NS NS 1 NS NS NS NS NS

NS NS 0.58*** 0.33* 0.33** 0.52*** NS 0.50*** 0.42**

NS NS NS 0.37* NS NS NS NS NS

NS NS 0.61*** NS 0.73*** 0.53*** NS 0.67*** 0.69***

NS NS 0.85*** NS 0.64** 0.87*** NS NS 0.60**

Soil moisture (SM), total soluble nitrogen (TSN), organic matter (OM), CO2 evolution, microbial biomass (MB), Shannon index (H ), qCO2 , and microorganism utilization ability of carboxylic acids (CA), carbohydrates (Carb), aromatic carboxylic acids (ACA), amino acids (AA), and community level physiological profile (CLPP). NS, not significant (p > 0.05). * p < 0.05. ** p < 0.01. *** p < 0.0001.

H' 0

0

0.5

1

1.5

2 a

a

a

5 10

b

a

2.5 I

a

II III

20 a

a

25

IV

30

Soil layer

Depth (m)

15

35 a

40

a

V

45 50

a

a

VI

CSL Control

Fig. 5. Changes in mean values of soil microbial diversity (H ) along a vertical profile in soil from a cattle-slurry lagoon (CSL) and control site. Parallel soil layers marked with different letters indicate significant differences (p < 0.05). Fig. 4. Changes in mean CLPP values of soil samples collected from a cattle-slurry lagoon (CSL) (A) and from a control site (B) along a vertical profile. Parallel soil layers marked with different letters indicate significant differences (p < 0.05). AA = amino acid; ACA = aromatic carboxylic acid; Carb = carbohydrates; CA = carboxylic acid.

and 0 ␮gCO2 -C g dry soil−1 h−1 , respectively). The significantly (p < 0.05) higher value of ACA (31.48 ␮gCO2 -C g dry soil−1 h−1 ) was found in soil layer V, while the lowest value was detected in soil layer I (1.2 ␮gCO2 -C g dry soil−1 h−1 ) (Table 5). The vertical profile of substrate utilization by the microbial community at the control site reveals a different pattern from that obtained at the CSL site. Soil layer V exhibited significantly (p < 0.05) higher utilization of amino acids (5.4 ␮gCO2 -C g dry soil−1 h−1 ) compared to soil layers I, III, IV, and VI, with values of 1.2, 0.3, 0.2, and 1.2 ␮gCO2 -C g dry soil−1 h−1 , respectively. There were no significant differences in ACA along the vertical profile. In soil layer VI, significantly (p < 0.05) higher carbohydrate utilization was detected (3.1 ␮gCO2 -C g dry soil−1 h−1 ) compared to layers I, II, III, and IV, with values of 0.77, 0.51, 0.24, and 0.3 ␮gCO2 -C g dry soil−1 h−1 , respectively. In soil layer V, significantly (p < 0.05) higher utilization of CA (26.7 ␮gCO2 -C g dry soil−1 h−1 ) was detected compared to soil layers I, II, III, and IV (4.55, 6.01, 1.28, and 0 ␮gCO2 -C g dry

soil−1 h−1 , respectively). CLPP was found to be significantly affected by sampling site (p = 0.043) and soil layer (p = 0.04). 3.7. Microbial functional diversity (H ) H ranged between 2.03 and 1.5 in soil layers I and VI, respectively, in soil samples obtained from the CSL, in comparison with values of 1.96 and 1.02 in samples obtained from the control site. The comparison of parallel soil layers from CSL and the control site revealed a significant difference between sites at soil layer III, in which H values were significantly (p < 0.05) higher in the CSL site and were calculated as 1.73 and 1.02, respectively (Fig. 5). The highest H values were found in soil layers I (2.03) and IV (1.96) for the CSL and control site, respectively. The lowest H values were found in soil layer VI (1.5) and in soil layer III (1.02) for the CSL and control site, respectively. The H values changed along the different soil layers in CSL to significant differences between them. Soil layers I, II, and V had significantly (p < 0.05) higher values of H compared to soil layer VI, while the intermediate soil layers III and IV did not show significantly different H values compared to the above-mentioned soil layers (Table 5). In contrast to the description of H values at the CSL site, there were no significant differences in H values between the different soil layers at the control site (Table 6).

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G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39

H values were found to be significantly affected (p = 0.014) by soil layer (Table 3). Moreover, H values in the CSL were found to be correlated with CO2 evolution values (p < 0.0001, r2 = 0.58), with MB values (p < 0.05, r2 = 0.33), with the different carbon substrates (CA–p < 0.01, 0.33; Carb–p < 0.0001, r2 = 0.52; and AA–p < 0.0001, r2 = 0.50), and with the community physiological activity (p < 0.001, r2 = 0.42). At the control site, H was correlated with MB (p < 0.05, r2 = 0.37) (Table 7).

4. Discussion The present paper was limited to investigating the vertical dispersion and long-term impact of slurry from a dairy farm on a soil microbial community. The effect of slurry on the nitrate, chloride and steroidal hormone concentrations has been previously described (Arnon et al., 2008). SM percentage and OM are known to be the most important factors affecting soil biotic activity in general and the microbial community in particular. In the present work, it was found that there was a high level of SM in the interface between the lagoon and the upper soil layers. Such results would be expected from the long-term (30 years) continuous vertical flow of wet cattle slurry to the soil. This increased SM was positively associated with an increase in MB. Hoffmann et al. (2002) described the importance of long-term organic fertilization amendments in elevating soil OM content. More recently, Fliessbach et al. (2007) investigated soil quality in organic and conventional agricultural managements and biological activity as indicators. They found that soil OM was positively affected by long-term manure amendments to soil, which would agree with our findings. However, results obtained in the present study showed that the percentage of OM was higher in the upper layers (I-II) in the control compared to the CSL sites. This may be the result of the contribution of above- and below-ground components of primary production that became exploited by the biotic community via mineralization, minimizing vertical flow of OM to the deeper soil layers. At the CSL site, with a high and continuous flow of OM, an increase in OM in the deeper soil layers was observed. In addition to the rising OM, cattle-manure applications led to increased nitrogen concentrations in soil, similar to the findings of Lithourgidis et al. (2007) and Dordas et al. (2008). Similarly, Decau et al. (2004) found that cattle-urine fertilization increases nitrate leaching up to 70 cm, while Vellidis et al. (1996) found nitrate at 3 and 6 m depths as a result of manure dropped by grazing animals. Our results show that total soluble nitrogen (TSN) values at the CSL site were consistently significantly higher throughout the soil vertical profile (layers I–VI). Similar findings previously described for this site in Arnon et al. (2008) were determined independently. It seems that nitrogen was correlated with SM, which contributed to the infiltration of TSN throughout the soil layers. Moreover, it was found that TSN positively affected MB. This would agree with Zhang and Zak (1998), who suggested that microbial biomass can increase following moisture input only if there is sufficient available N. The long-term cattle-slurry accumulation had a positive effect on MB. We found significantly higher levels of MB in the CSL (more than threefold higher) compared to the control site. These results agree with similar studies that demonstrated the positive effect of organic amendments on microbial biomass (Dhull et al., 2004; Jedidi et al., 2004). Moreover, in the present study, MB vertical distribution was found to be clearly different in the CSL as opposed to the reference site. The difference was primarily in utilization ability, which in turn was strongly correlated with OM availability. There was a transformation of the soil microbial-community composition beneath the CSL compared to the reference site. Sim-

ilar findings presented in de Freitas et al. (2003) showed that cattle manure changed the soil microbial-community structure. Saviozzi et al. (2006) and Ahamadou et al. (2009) showed that the presence of cattle manure improves enzymatic activity and substrate-utilization ability. Furthermore, Kandeler et al. (1999) showed that long-term buried organic materials can affect the activity rate of soil microorganisms. Since we found that MB was closely correlated with functional diversity, we suggest that the soil microbial functional diversity was also different between the two compared sites. Other archaea were present in the soil under the CSL. Oxidizing ammonia (AOA) was abundant in all soil layers (AOA amoA 107 copies g−1 soil) but only a preliminary report has been made to date (Sher et al., 2009). The microbial community at the CLS site displayed better utilization ability of carboxylic acids in the deeper soil layers (III, IV) than in parallel layers at the control site. This can be explained by the infiltration of the water-soluble organic acids that originated in the slurry, throughout the soil layers. In addition, the microbial community at the CLS site consumed ACA at a significantly higher level than the community at the control site. This could be adaptation to substrate availability since these compounds are plentiful in cattle slurry. That the microbial community can utilize these compounds in slurry is evidenced from the work of McGill and Jackson (1977) who found that organic carboxylic acids from stored pig slurry declined to low steady values. Patni and Jui (1985) found the same result for volatile fatty acids in stored dairy-cattle slurry. We conclude that anthropogenic activities, in particular the long-term accumulation of cattle manure on a soil surface, can have an impact on a soil microbial community. These activities can be detected from the topsoil to the groundwater at 50 m. The impacts are characterized by altered microbial biomass and substrate utilization ability, which indicate that the functional diversity of the soil microbial community has changed. We, therefore, suggest that the soil microbial community can be used as a bioindicator for micropollutants released as a result of human activities even at depths below the rhizosphere. This potential of the soil microbial community to act as bioindicators is not necessarily limited to narrow areas of anthropogenic activities but may have implications for larger changes resulting from global warming. Acknowledgements We would like to thank Ms. Gineta Barness for technical help and Ms. Sharon Victor for help in preparing the manuscript for publication. References Ahamadou, B., Huang, Q.Y., Chen, W.L., Wen, S.L., Zhang, J.Y., Mohamed, I., Cai, P., Liang, W., 2009. Microcalorimetric assessment of microbial activity in longterm fertilization experimental soils of Southern China. FEMS Microbiol. Ecol. 70, 186–195. Anderson, J.P.E., Domsch, K.H., 1978. Physiological method for quantitative measurement of microbial biomass in soils. Soil Biol. Biochem. 10, 215–221. Arnon, S., Dahan, O., Elhanany, S., Cohen, K., Pankratov, I., Gross, A., Ronen, Z., Baram, S., Shore, L.S., 2008. Transport of testosterone and estrogen from dairy-farm waste lagoons to groundwater. Environ. Sci. Technol. 42, 5521–5526. Berg, N., Steinberger, Y., 2008. Role of perennial in determining the activity of the microbial plants community in the Negev Desert ecosystem. Soil Biol. Biochem. 40, 2686–2695. Berg, N., Steinberger, Y., 2010. Are biological effects of desert shrubs more important than physical effects on soil microorganisms? Microb. Ecol. 59, 121–129. Campbell, C.D., Chapman, S.J., Cameron, C.M., Davidson, M.S., Potts, J.M., 2003. A rapid microtiter plate method to measure carbon dioxide evolved from carbon substrate amendments so as to determine the physiological profiles of soil microbial communities by using whole soil. Appl. Environ. Microbiol. 69, 3593–3599. Carpenter-Boggs, L., Kennedy, A.C., Reganold, J.P., 2000. Organic and biodynamic management: effects on soil biology. Soil Sci. Soc. Am. J. 64, 1651–1659. de Freitas, J.R., Schoenau, J.J., Boyetchko, S.M., Cyrenne, S.A., 2003. Soil microbial populations, community composition, and activity as affected by repeated appli-

G. Hermann et al. / Applied Soil Ecology 49 (2011) 32–39 cations of hog and cattle manure in eastern Saskatchewan. Can. J. Microbiol. 49, 538–548. Decau, M.L., Simon, J.C., Jacquet, A., 2004. Nitrate leaching under grassland as affected by mineral nitrogen fertilization and cattle urine. J. Environ. Qual. 33, 637– 644. Dhull, S., Goyal, S., Kapoor, K., Mundra, M., 2004. Microbial biomass carbon and microbial activities of soils receiving chemical fertilizers and organic amendments. Arch. Acker. Pfl. Boden 50, 641–647. Dordas, C.A., Lithourgidis, A.S., Matsi, T., Barbayiannis, N., 2008. Application of liquid cattle manure and inorganic fertilizers affect dry matter, nitrogen accumulation, and partitioning in maize. Nutr. Cycl. Agroecosys. 80, 283–296. Ebersberger, D., Werrnbter, N., Niklaus, P.A., Kandeler, E., 2004. Effects of long term CO2 enrichment on microbial community structure in calcareous grassland. Plant Soil 264, 313–323. Fitzpatrick, E.A., 1996. An Introduction to Soil Science, second ed. Longman Singapore Publishers, London. Fliessbach, A., Oberholzer, H.R., Gunst, L., Mader, P., 2007. Soil organic matter and biological soil quality indicators after 21 years of organic and conventional farming. Agric. Ecosyst. Environ. 118, 273–284. Gal, M., Amiel, A.J., Ravikovitch, S., 1974. Clay mineral distribution and origin in soil types of Israel. J. Soil Sci. 25, 79–89. Hoffmann, S., Csitari, G., Hegedus, L., 2002. The humus content and soil biological properties as a function of organic and mineral fertilization. Arch. Acker. Pfl. Boden 48, 141–146. Houba, V.J.G., Novozamsky, I., Vittenbogaard, J., Van Der Lee, J.J., 1987. Automatic determination of total soluble nitrogen in soil extracts. Landwirt. Forsch. 40, 295–302. Jedidi, N., Hassen, A., van Cleemput, O., M’Hiri, A., 2004. Microbial biomass in a soil amended with different types of organic wastes. Waste Manage. Res. 22, 93– 99. Kandeler, E., Stemmer, M., Klimanek, E.M., 1999. Response of soil microbial biomass, urease and xylanase within particle size fractions to long-term soil management. Soil Biol. Biochem. 31, 261–273. Kohler, F., Hamelin, J., Gillet, F., Gobat, J.M., Buttler, A., 2005. Soil microbial community changes in wooded mountain pastures due to simulated effects of cattle grazing. Plant Soil 278, 327–340. Lee, L.S., Carmosini, N., Sassman, S.A., Dion, H.M., Sepulveda, M.S., 2007. Agricultural contributions of antimicrobials and hormones on soil and water quality. Adv. Agron. 93, 1–68. Lithourgidis, A.S., Matsi, T., Barbayiannis, N., Dordas, C.A., 2007. Effect of liquid cattle manure on corn yield, composition, and soil properties. Agron. J. 99, 1041–1047. McGill, A.E.J., Jackson, N., 1977. Changes in short-chain carboxylic-acid content and chemical oxygen-demand of stored pig slurry. J. Sci. Food Agric. 28, 424–430.

39

Patni, N.K., Jui, P.Y., 1985. Volatile fatty acids in stored dairy-cattle slurry. Agric. Wastes 13, 159–178. Ravikovitch, S., 1981. The soils of Israel: formation. In: Nature and Properties, first ed. Hakibbutz Hameuchad Publishing House, Tel Aviv (in Hebrew). Rillig, M.C., Scow, K.M., Klironomos, J.N., Allen, M.F., 1997. Microbial carbonsubstrate utilization in the rhizosphere of Gutierrezia sarothrae grown in elevated atmospheric carbon dioxide. Soil Biol. Biochem. 29, 1387–1394. ˜ ˜ ˜ J., Proupin-Castineiras, J., Villanueva-López, M., Núnez-Fernández, Rodríguez-Anón, O., 2007. Development of an experimental procedure to analyse the ‘soil health state’ by microcalorimetry. J. Therm. Anal. Calorim. 87, 15–19. Rowell, D.L., 1994. Soil Science: Methods and Applications. Longman Group UK Ltd., London. S.F.A.S., 1995. Manual-San Plus Analyzer. SKALAR Analytical, The Netherlands. Saul-Tcherkas, V., Steinberger, Y., 2009. Substrate utilization patterns of desert soil microbial communities in response to xeric and mesic conditions. Soil Biol. Biochem. 41, 1882–1893. Saviozzi, A., Cardelli, R., N’kou, P., Levi-Minzi, R., Riffaldi, R., 2006. Soil biological activity as influenced by green waste compost and cattle manure. Compos. Sci. Util. 14, 54–58. Shahar, A.E. (Ed.), 2009. The New Israeli Atlas: National Atlas. The Israeli Mapping Center Publisher, Israel. Sher, Y., Baram, S., Dahan, O., Ronen, Z., Nejidat, A., 2009. Diversity and abundance of bacterial and archaeal ammonia oxidizers in hypernutrified soils under a dairy farm manure pond. FEMS 2009: Microbes and Man - Interdependence and Future Challenges, Gothenburg, Sweden, June 28–July 2, 2009 (Abstract). Shore, L.S., Pruden, A. (Eds.), 2009. Hormones and Pharmaceuticals Generated by Concentrated Animal Feeding Operations: Transport in Water and Soil (Emerging Topics in Ecotoxicology). Springer, New York. Steinberger, Y., Shore, L.S., 2009. Soil ecology and factors affecting biomass. In: Shore, L.S., Pruden, A. (Eds.), Hormones and Pharmaceuticals Generated by Concentrated Animal Feeding Operations: Transport in Soil and Water. Springer, New York, pp. 53–61. Vellidis, G., Hubbard, R.K., Davis, J.G., Lowrance, R., Williams, R.G., Johnson, J.C., Newton, G.L., 1996. Nutrient concentrations in the soil solution and shallow groundwater of a liquid dairy manure land application site. Trans. ASAE 39, 1357–1365. Williams, B.L., Grayston, S.J., Reid, E.J., 2000. Influence of synthetic sheep urine on the microbial biomass, activity and community structure in two pastures in the Scottish uplands. Plant Soil 225, 175–185. Zak, J.C., Willig, M.R., Moorhead, D.L., Wildman, H.G., 1994. Functional diversity of microbial communities: a quantitative approach. Soil Biol. Biochem. 26, 1101–1108. Zhang, Q., Zak, J.C., 1998. Effects of water and nitrogen amendment on soil microbial biomass and fine root production in a semi-arid environment in West Texas. Soil Biol. Biochem. 30, 39–45.