- Email: [email protected]
Impact of cattle grazing and inorganic fertiliser additions to managed grasslands on the microbial community composition of soils
Applied Soil Ecology 31 (2006) 73–82 www.elsevier.com/locate/apsoil
Impact of cattle grazing and inorganic fertiliser additions to managed grasslands on the microbial community composition of soils Christopher D. Clegg * Institute of Grassland and Environmental Research, North Wyke, Okehampton, Devon EX20 2SB, UK Received 25 October 2004; received in revised form 10 April 2005; accepted 12 April 2005
Abstract A study was undertaken to determine if cattle grazing on managed grasslands had an impact on the microbial community composition of soils. Microbial community molecular profiles of bacteria, actinomycetes, pseudomonads and fungi were generated by polymerase chain reaction (PCR) amplification of rDNA sequences from community DNA isolated from soils. PCR products were profiled using denaturing gradient gel electrophoresis (DGGE) and analysed by principal co-ordinate analysis. PCR–DGGE profiles indicated that cattle grazing had an impact on the pseudomonad community structure only, and that the addition of inorganic nitrogen (N) fertiliser impacted on bacterial, actinomycete and pseudomonad community structure. There was no difference in the community profiles of fungi from grazed and N fertilised grassland plots. Analysis of phospholipid fatty acid (PLFA) profiles revealed that both cattle grazing and N fertiliser impacted on microbial community structure. The abundance of individual PLFAs differed between treatments, with bacterial (15:0), actinomycete (10Me18:0) and fungal (18:2v6) PLFAs not affected directly by grazing cattle and N fertiliser, however, there were significant grazing–fertiliser interactions. Bacterial plate counts were highest in the N fertilised plots and fungal plate counts were highest in the cattle grazed plots. Analysis of molecular microbial community profiles with PLFA and background soil data revealed several significant correlations. Notably, soil pH was positively correlated with PCO1 of the pseudomonad community profiles and negatively correlated with the fungal PLFA 18:2v6. Fungal DGGE profiles were negatively correlated with the fungal PLFA 18:2v6, and bacterial and fungal plate counts positively correlated with each other. Correlation analysis using PC1 from PLFA profile data showed no significant relationship with soil organic matter, pH, total C and total N. The results indicate that cattle grazing and N fertiliser addition to grasslands impact on the community composition of specific groups of micro-organisms. The consequences of such changes in population structure may have implications regarding the dynamics of nutrient turnover in soils. # 2005 Elsevier B.V. All rights reserved. Keywords: Grazing; Grasslands; Micro-organsims; Molecular profiling; Bacteria; Fungi
1. Introduction * Tel.: +44 1837 883532; fax: +44 1837 82139. E-mail address: [email protected].
Micro-organisms play a key role in grassland ecosystems through regulating the dynamics of
0929-1393/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2005.04.003
74
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
organic matter decomposition and plant nutrient availability. Whilst there is considerable information available concerning the impact of both animal grazing and inorganic fertiliser application on communities of macro-fauna and flora, the effects on microbial community composition in soils have received little attention. Previous studies have tended to focus on the effects of cattle urine and faeces on soil processes, e.g. nitrification, denitrification, soil respiration, microbial biomass (e.g. Lovell and Jarvis, 1996a,b; Hatch et al., 2000), and issues related to potential pathogen movement in soils (e.g. Vinten et al., 2002), however, little seems to be known about the impact of above ground animal grazing on the microbial community composition of agricultural grassland soils. There is clearly a need to further our understanding of the microbiology of grassland soils given that in the U.K., about 50% (Gordon and Duncan, 1993) of the land area comprises agricultural grassland and 35% of the land area is grazed (DEFRA, 2002). In order to maintain the productivity of these grasslands, inorganic nitrogen (N) fertiliser is applied to about 85% of agricultural grasslands in the U.K. (Hopkins and Hopkins, 1993) to meet the demands of grazing animals. One of the reasons for the paucity of microbiological studies on grazed grasslands may be that studies were traditionally limited by the resolution of the available methodologies. One of the problems associated with the study of soil microbiology was that most bacteria, and an unknown proportion of fungi, could not be readily isolated which thus impaired our understanding of community composition. However, microbial community based methodologies such as DNA and PLFA profiling approaches can now circumvent the problems associated with culturing. Advances in molecular community profiling approaches can provide information regarding the community composition of microbial populations in soils, for example, through the isolation of microbial DNA from soil, community profiles for bacteria (Muyzer et al., 1993) and fungi (van Elsas et al., 2000) can be generated through the PCR amplification of 16S and 18S rRNA genes, respectively, and molecular community profiles compared through DGGE. The objective of this study was to determine if cattle grazing and N fertiliser application to managed grasslands had an impact on the microbial community
composition of the soils. This was undertaken through molecular profiling of the eubacterial, actinomycete, pseudomonad and fungal communities of these soils together with PLFA profiling and the determination of some soil background characteristics.
2. Materials and methods 2.1. Soils Soils were sampled from the Rowden long-term experimental site at the Institute of Grassland and Environmental Research (IGER), North Wyke Research Station, Devon in SW England (NGR SX 650 995). These swards had been under long-term pasture for the previous 50 years and under the current management regimes for the past 15 years. The treatments analysed in this study where cattle grazing and inorganic N fertiliser in the following combinations: ungrazed and unfertilised (UG–O), grazed and unfertilised (G–O), grazed and fertilised at 280 kg inorganic N (ha yr)1 (G–N), and ungrazed and fertilised at 280 kg inorganic N (ha yr)1 (UG–N). The stocking density for cattle was four steers ha1 and was managed accordingly to maintain a sward height of about 7.5 cm. The grass in the ungrazed plots was cut and removed three times during the growing season. The soil is a poorly drained silty clay loam of the Hallsworth series. Soil samples were taken as follows: about 10–12 mm 25 mm 50 mm deep cores were taken from each of random triplicate quadrats within a single ha1 plot of each of the four different management treatments. Soils were sieved through a 4 mm mesh sieve. Total C and total N contents were obtained with an automated Dumas procedure on a Carlo Erba NA2000 elemental analyser (CE Instruments) and soil pH (water), organic matter content (loss of weight on ignition) and bulk density were also determined (Lovell et al., 1995). 2.2. Bacterial and fungal plate counts Numbers of culturable bacteria and fungi were determined by plating samples onto solid media. About 0.5 g (fresh wt.) of each replicate soil sample was added to 1.8 ml 0.1% sodium pyrophosphate in an Eppendorf tube and mixed by vortexing. Ten-fold
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
serial dilutions were made in sterile 0.1% sodium pyrophosphate and 100 ml aliquots of diluted soil suspension were spread-plated onto 10% tryptone soya agar (0.1 TSA) to determine bacterial plate counts. To determine fungal plate counts, 100 ml aliquots of the soil serial dilutions were spread-plated onto potato dextrose agar (PDA) containing streptomycin (50 mg ml1) to suppress bacterial growth. Agar plates were maintained at 15–17 8C for 5 days before counting numbers of colony forming units (cfu). 2.3. Isolation of total DNA from soils To about 1.0 g (fresh weight) soil was added 1.0 g 0.1 mm diam. zirconia/silica beads (BioSpec. Products Inc.) and 400 ml guanidinium thiocyanate solution (4 M guanidinium thiocyanate, 0.5% sarkosyl, 0.25 M sodium citrate, pH 7.0). Samples were then processed in a Mini-beadbeater (Biospec Products Inc.) at 5000 rpm for 60 s and the soil suspension centrifuged at 13,000 rpm (MSE Micro Centaur, U.K.) for 1 min. The supernatant was mixed with an equal volume of phenol (pH 8.0) and centrifuged at 13,000 rpm for 5 min. The upper aqueous phase was mixed with an equal volume of chloroform and centrifuged at 13,000 rpm for 5 min. To precipitate out nucleic acids, 0.1 vol of 5 M NaCl and 2.5 vol of 100% ethanol were added to the aqueous phase and centrifuged at 13,000 rpm for 30 min. The resultant pellet was then washed twice in 70% ethanol and dried. The dried pellet was resuspended in sterile distilled water. The amounts of DNA isolated from the different soils were determined colorimetrically by reaction with diphenylamine (Lichtenstein and Draper, 1985). 2.4. PCR amplification of 16S and 18S rDNA PCR amplification was carried out to generate products for molecular population profiling of the bacterial, actinomycete and fungal communities. For profiling the bacterial communities, PCR products were generated using total community DNA as the template for amplification of partial 16S rRNA gene sequences. To generate molecular profiles of the actinomycete and fungal community structure a nested PCR approach was adopted, whereby the first
75
round of PCR used total community DNA as the template, and then the second round of PCR used the products from the first round of the nested PCR as the template. All PCR amplifications were carried out in a 40 ml reaction volume containing 20 pmol of each primer, 250 mM dNTPs, 3 U Expand High Fidelity polymerase (Roche Diagnostics, U.K.), 4 ml 10 reaction buffer. For the amplification of 16S rRNA genes and the first round of nested PCR for the actinomycete and fungal community profiles, about 50 ng of total community DNA isolated from soil was used as the template for amplification and each reaction also contained 16 mg bovine serum albumin (Roche Diagnostics, U.K.). PCR amplification of the 16S rRNA eubacterial genes was carried out using the primers 341f-GC and 534r (Muyzer et al., 1993). The GC clamp (CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG) was attached to the 50 -end of the forward primer. PCR was performed using the following cycle, 95 8C for 5 min followed by 35 cycles of 95 8C for 1 min, 55 8C for 1 min, 72 8C for 2 min. A final extension time of 10 min at 72 8C was included. For the actinomycetes, the primers F243 and R1378 (Heuer et al., 1997) were used in conjunction with the following cycle of 95 8C for 5 min followed by 35 cycles of 95 8C for 1 min, 63 8C for 1min, 72 8C for 2 min. This was followed by a final extension time of 10 min at 72 8C. The products from the first round of PCR were then run on a 1% low melting point agarose gel (Roche Diagnostics), stained in ethidium bromide and visualised under ultraviolet light. Bands of the estimated product sizes were excised from the gel, melted at 70 8C and 1 ml was added to the reaction mix for the second round of PCR using the primers 341f-GC and 534r. The cycle used for the second round of PCR was the same as that described earlier for the eubacterial primers. To generate PCR products for fungal community profiling, the first round of nested PCR used the primer pair EF4 and Fung5r (van Elsas et al., 2000) with the following thermal cycle, 95 8C for 5 min, 40 cycles of 95 8C for 1 min, 48 8C for 1 min, 72 8C for 2 min and a final extension at 72 8C for 5 min. The second round of nested PCR used 0.2 ml of the products from the first round of nested PCR as the target sequence with primers NS2f and Fungi5rGC (van Elsas et al., 2000) using the following cycle, 95 8C for 5 min, 30 cycles at 95 8C for 1 min, 55 8C for 30 s, 72 8C for 1 min and a
76
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
final extension of 72 8C for 5 min. All PCR samples were amplified with a Primus Thermocycler (MWGBiotech, U.K.) and final PCR products were checked on a 1.2% agarose gel stained with ethidium bromide.
an indicator of fungal biomass (Federle, 1986). Other PLFAs determined were i14:0, 14:0, 16:0, 16:1v7, 17:1v6, nMe18:0, 18:0, trans18:1v9 and 20:0. 2.7. Banding pattern analysis and statistics
2.5. Molecular profiling of soil bacterial and fungal population structure PCR products were resolved using DGGE to provide molecular profiles of bacterial and fungal communities. For the generation of bacterial community profiles, polyacrylamide gels (8% acrylamide, 0.5 TAE, 37:1 acrylamide:bisacrylamide) were cast using 40–55% denaturant (100% denaturant was defined as 7 M urea with 40% [vol/vol] formamide). For the fungal community structure profiles, a denaturant range of 45–55% was used. PCR products were loaded into the lanes of the gel in a random order to avoid any potential bias in the later analysis. The gel was run using a DCode system (Bio-Rad Laboratories) at a constant temperature of 60 8C and at 60 V for 16 h. After electrophoresis, gels were fixed for at least 2 h in a solution of 10% ethanol and 0.5% acetic acid. The gels were then stained in a solution of 0.1% (wt/ vol) silver nitrate for 20 min before briefly rinsing and developing (0.02 g NaBH4, 0.8 ml formaldehyde, 200 ml 1.5% [wt/vol] NaOH) until the bands appeared. Gels were then fixed in 0.75% Na2CO3 for 10 min before scanning with a Hewlett Packard Scanjet 5370C. Banding patterns were determined using Phoretix 1D Gel Analysis Software, Version 4.0 (Phoretix International, Newcastle Upon Tyne, U.K.).
Similarity indices of PCR–DGGE molecular profiles for bacterial and fungal communities were determined using binary data only. Similarity matrices were generated from binary data for each lane using the Jaccard coefficient as previously described (Clegg et al., 2003). The similarity indices were used in principal co-ordinate analysis (PCO) and the first 6 PCOs (typically accounting for about 70–80% of the variability) were then analysed by two-way MANOVA (multivariate analysis of variance, Genstat fifth edition) to determine statistical differences in the bacterial and fungal community profiles. For the analysis of PLFA data, the amounts (nmol g1 dry soil) were log transformed and analysed initially by principal component (PC) analysis to reduce the dimensionality. The first three principal components (accounting for 96.6% of the variability) were analysed by two-way MANOVA to determine treatment effects on the PLFA composition of the soils. Two-way analysis of variance was also used to determine treatment related effects on amounts of individual PLFAs isolated from different plots. Correlation analyses were conducted on PCOs 1 and 2 and PCs 1 and 2 with individual PLFAs, plate counts and background soil data. Results were considered significant at P 0.05.
2.6. Phospholipid fatty acid analysis 3. Results PLFAs were extracted, fractionated and quantified from replicate 2 g soil samples and analysed as previously described (Clegg et al., 2003) using the method of Bardgett et al. (1996), which is based on the method of Bligh and Dyer (1959). Fatty acid methyl esters were identified by chromatographic retention time and compared to a standard qualitative mix (Supelco UK, Poole, Dorset, UK). Fatty acid nomenclature was as follows: fatty acids i15:0, a15:0, 15:0, i16:0, 17:0, i17:0, cy17:0, cis18:1v7 and cy19:0 represented current known bacterial PLFAs (Frostega˚rd et al., 1993), 10Me18:0 was indicative of actinomycetes and 18:2v6 was used as
Cattle grazing and fertiliser N application had some impact on the background soil characteristics (Table 1). Total carbon (% content) was significantly greatest in the grazed plots (P = 0.03), and whilst, % organic matter was also highest in the grazed plots, this was not significantly greater than ungrazed plots. Neither grazing nor fertiliser N had an effect on the total N (%) content of the soils, however, those soils that received fertiliser did have significantly lower pH values (P = 0.03). Bacterial plate counts were significantly higher (P = 0.02) in the fertilised soils than the unfertilised
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
77
Table 1 Means (standard errors) of background soil characteristics (n = 3) Treatment
Soil pH
Organic matter (%)
Total carbon (%)
Total nitrogen (%)
Grazed N Grazed + N Ungrazed N Ungrazed + N
5.85 5.72 6.02 5.43
14.0 14.2 12.9 13.7
6.65 7.32 5.91 6.43
0.66 0.71 0.63 0.66
(0.10) (0.11) (0.09) (0.19)
(1.12) (0.43) (0.76) (0.29)
(0.41) (0.34) (0.23) (0.24)
(0.03) (0.06) (0.03) (0.02)
N: unfertilised; +N: fertilised with inorganic nitrogen.
soils, and grazing was not a significant factor. In the fertilised soils, mean bacterial plate counts (per gram dry soil) were 2.09 107 and 2.56 107 in the grazed and ungrazed treatments and 1.11 107 and 0.94 107 for the unfertilised grazed and ungrazed treatments. Fungal plate counts were significantly higher (P = 0.05) in the ungrazed soils, whilst, fertiliser effect was not significant. Mean colony forming units (per gram dry soils) for the ungrazed soils were 4.26 105 (fertilised) and 1.8 105 (unfertilised) and in the grazed soils mean numbers of cfus were 0.93 105 (fertilised) and 1.36 105 (unfertilised). Bacterial and fungal plate counts were significantly positively correlated. Total microbial DNA was readily isolated from all soils with amounts varying from about 59 to 115 mg g1 soil. Amounts of DNA isolated from soils were not influenced by either grazing or inorganic N fertiliser. All DNA samples were readily amplified by PCR and molecular profiles for eubacteria, actinomycete, pseudomonad and fungal communities generated. Many of the banding patterns were complex and variable between replicates. Statistical analysis was conducted on the first 6 PCOs, and for the purpose of illustration, the relative community structures are represented by the ordination plots in Fig. 1, where PCOs 1 and 2 typically represent 14–19 and 13–15% of the variation. The total numbers of different banding positions between gel lanes analysed were 132 bands for the eubacterial profiles, 117 actinomycete bands, 94 pseudomonad bands and 69 different fungal bands. MANOVA of the first 6 PCOs revealed that cattle grazing had an impact on the pseudomonad community structure (P = 0.01) only. However, ANOVA of the individual PCOs also revealed that cattle grazing was the discriminant in PCO2 of the actinomycete community profiles (P = 0.02). MANOVA of the first 6 PCOs indicated that inorganic N fertiliser impacted on the community
structures of the eubacteria (P = 0.002), actinomycetes (P = 0.05) and pseudomonads (P = 0.02) but not the fungi. There was also a significant grazing– inorganic N interaction for the pseudomonad community structure (P = 0.02). The amounts of PLFAs isolated from soils varied considerably, from about 50–400 nmol g1 dry soil, however, these amounts were not influenced by either cattle grazing or inorganic N fertiliser. For all PLFAs combined, MANOVA of the first 6 PCOs (92% variation) indicated that cattle grazing (P = 0.02), inorganic N fertiliser (P = 0.006) and the interaction (P = 0.008) had significant effects on the overall community profiles (Fig. 2). The Gram positive bacterial PLFA i17:0 was significantly higher in both grazed and fertilised soils, and amounts of those PLFAs indicative of the actinomycetes (10Me18:0) and fungi (18:2v6) were not affected by both cattle grazing and inorganic nitrogen fertiliser alone. There were significant grazing–fertiliser interactions on the PLFAs 14:0, 15:0, i16:0, 16:0, 16:1v7, 17:0, i17v6, 10Me18:0, 18:0, 18:2v6, 20:0. Analysis of PLFA loadings from the principal component analysis indicated that PLFAs i15:0, trans18:1v9 and i17:0 were outliers responsible for some of the determined differences due to different treatments. PLFA i15:0 is indicative of Gram positive bacteria and amounts were only significantly higher in the grazed unfertilised soils. Trans18:1v9 is indicative of Gram negative bacteria and was also highest in grazed and unfertilised soils. Correlation analysis was also undertaken using the first two principal co-ordinates from the PCR–DGGE and PLFA profiles. PCR–DGGE PCOs 1 and 2 typically accounted for 14–18 and 12–14% of the variability, respectively, whilst, PLFA PC1 and PC2 accounted for 73.1 and 14.7%, respectively. Significant positive correlations were obtained between eubacterial PCO1 and bacterial plate counts
78
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
Fig. 1. (a–d) Plots of PCO1 and PCO2 means (standard error) produced from the multivariate analysis of (a) eubacterial, (b) actinomycete, (c) pseudomonad and (d) fungal PCR–DGGE banding profiles from ungrazed–unfertilised (*), grazed–unfertilised (*), ungrazed–N fertilised (~) and grazed–N fertilised (~) grassland soils.
(P = 0.035), pseudomonad PCO1 with soil pH (P = 0.017) and for actinomycete PCO1 with PLFA i15:0 (P = 0.04). Significant negative correlations were obtained between actinomycete PCO1 and PLFA i17:0 (P = 0.02), pseudomonad PCO2 and both PLFA i15:0 (P = 0.043) and fungal plate counts (P = 0.047),
fungal PCO1 and fungal PLFA 18:2v6 (P = 0.035), and PLFA PC2 and bacterial plate counts (P = 0.031). Correlation analysis of PLFA PC1 and soil characteristics revealed that there were no significant associations between PC1 and soil organic matter, pH, total N, total C, bacterial and fungal plate counts. Total soil C was significantly positively correlated with PLFA i17:0 (P = 0.025), DNA (P = 0.034), organic matter (P = 0.004), and total N was significantly positively correlated with DNA (P = 0.003) and organic matter (P = 0.005). Soil pH was significantly negatively correlated with the fungal PLFA 18:2v6 (P = 0.01).
4. Discussion
Fig. 2. Plot of PC1 and PC2 means (standard error) produced from the multivariate analysis of PLFA profiles obtained from ungrazed– unfertilised (*), grazed–unfertilised (*), ungrazed–N fertilised (~) and grazed–N fertilised (~) grassland soils.
The main finding of this study was that both cattle grazing and inorganic N application to grasslands impacted on the community composition of microbial populations in managed soils. These results provide some evidence to part explain those previous studies reporting changes in transformation processes due to
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
cattle urine and faeces application to soils (e.g. Lovell and Jarvis, 1996a,b; Hatch et al., 2000). Grazing livestock can play an important role in the microbial ecology of grasslands through a series of specific factors associated with the presence of cattle. The management factors considered in this study were cattle grazing and inorganic N fertiliser application, however, in reality each of these events is a composite of several more specific, and possibly interactive, factors. For example, the practice of grazing cattle is a complex event and could comprise a range of specific factors such as faecal and urine deposition, shifts in rhizosphere exudation patterns resulting from defoliation effects of cattle grazing, shifts in botanical composition due to grazing and changes in soil structure and aerobicity due to animal compaction and poaching. Animal faeces and urine contain readily utilisable substrates and inputs into grasslands can result in changes in microbial activities. Inputs of cattle urine to soils have been reported to result in increases in respiration, N2O and NO2 emissions and an increase in microbial biomass (Lovell and Jarvis, 1996a). Within a grazed area, there are any number of urine patches of variable ages with differing amounts of mineral N present in the soil. In a previous study in an upland grassland soil, Ritz et al. (2004) reported a consistent trend of higher concentration notional urine patches with greater values of other soil chemical properties, microbial biomass and the abundance of many microbial PLFAs. The addition of synthetic sheep urine to soils was reported to immediately stimulate an increase of bacterial numbers, however, there were no effects on pseudomonad, fungal and yeast plate counts (Williams et al., 2000). The application of synthetic urine had a delayed effect on the utilisation of specific substrates, with activity greatest during the period 2–5 weeks after its addition to soil, indicating the contribution of urine to the patchiness of microbial activities and population composition in grazed grasslands. Cattle faeces contain soluble C, as well as small amounts of N and can stimulate increases in soil respiration and mineralisation processes (Hatch et al., 2000). An important point to consider when assessing the effect of the presence of animals on the microbiological quality of soils is that animal faeces deposited on the surface of the grazed paddock also contains a large concentration of micro-organisms.
79
Interpretation of results may become difficult, depending on the target group of micro-organisms because of difficulties discriminating those microbes in the soils, which are affected by the faecal deposit, and those that are merely introduced to the soil from within the faeces. Urine and faecal deposits from cattle may constitute between 3% (Antil et al., 2001) and 10% (White et al., 2001) of the surface area of a grazed grassland each year, however, up to about 14% of the daily faecal input from grazing animals can be washed away into watercourses during a rainfall event (Vinten et al., 2004). Whilst, it is difficult to assess the contribution of faecally introduced micro-organisms to the soil microbial community composition, their presence is inherent to grazing management. Taking into consideration the effects of rainfall on faeces through dissipation, dilution and run-off from fields, and the generally poor survival of faecally derived micro-organisms in soils, it is considered that in the context of this study the faecally introduced microorganisms contributed a minor unknown proportion of the soil microbial community composition detected. A feature of this study was the amount of variation between replicates in the PCR–DGGE banding patterns and PLFA analyses. Spatial variation is synonymous with field based studies and has previously been reported in phenotypic determinations on microbial communities such as metabolic (Garland and Mills, 1991) and fatty acid methyl ester profiling (Cavigelli et al., 1995), and also process based determinations (Parkin et al., 1987). In addition to phenotypic variation in soils, there is also some emerging evidence regarding the spatial composition of microbial communities based on DNA molecular studies at different scales. For example, using a broadscale molecular approach (Clegg et al., 2000), variation in the composition of microbial community DNA between replicate soil samples was sometimes found to be as great as the variation between treatment effects in upland grasslands, and that to a certain degree this may have obscured some treatment related effects. More recently, spatial heterogeneity has been reported to occur at the centimetre scale in upland grassland soils (Ritz et al., 2004) and also between different root regions of the same plant species (Clayton et al., 2005). The reasons for variability between replicate samples in this study are not clear,
80
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
however, in consideration of the findings of other studies it is likely that they are complex and attributable to many different factors within the soil environment. A reduction in botanical diversity (e.g. Tallowin, 1996) and shifts in the rates of some soil processes (e.g. Gill et al., 1995; Hatch et al., 2002; Lovell and Hatch, 1998) through the application of inorganic N fertiliser have previously been recognised, however, there is also emerging recent evidence that shifts in soil microbial community composition may also occur as a result of fertiliser amendment (Clegg et al., 2003; Gray et al., 2003; Kennedy et al., 2004). The mechanisms through which inorganic N fertiliser support changes in microbial community composition are not clear, and some may be interactive. Microbial community composition can be controlled by soil pH (Ba˚a˚th and Anderson, 2003), and whilst, many grassland soils are limed occasionally to counter the acidifying effects of inorganic N application, it is possible that localised pH changes occur in the soils as a result of fertiliser amendment. Changes in the botanical composition of grasslands through fertiliser N addition may indirectly impact on microbial community composition through the shift in the C quality and quantity of the plant material entering the soil. Also, the addition of inorganic N to soil may drive changes in the microbial community composition through direct competition of microbes for N as a substrate for growth or respiration purposes. The effects of defoliation through above ground herbivory of plants by cattle may also have an impact on the dynamics of microbial community structure and nutrient cycling within the rhizosphere through changes in the C balance. Defoliation can lead to increased losses of C (Paterson and Sim, 1999) and N (MacDuff and Jackson, 1992), and as a consequence, increases in microbial biomass (Holland, 1995; Mawdsley and Bardgett, 1997) and culturable bacteria (Mawdsley and Bardgett, 1997) in the rhizosphere of defoliated plants. Conversely, it has also been reported that defoliation can have no impact on microbial biomass (Mikola et al., 2001). The results of this study, and comparisons with others, suggest that the impact of agricultural management on the fungal communities in soils is unclear. In this present study, the abundance of the fungal PLFA 18:2v6 was not found to be influenced
by cattle grazing and N alone, however, there was a significant negative correlation with soil pH (higher abundance at lower pH), which was possibly a reflection of the slightly acidic pH optima for fungal activity generally. Interestingly, Bardgett et al. (1997) reported that the amount of fungal PLFA 18:2v6 was reduced when sheep were removed from an upland grassland and this was attributed to the concurrent cessation of liming and removal of readily utilisable inputs in the form of sheep excreta and urine and changes in the quality of plant root exudates. A greater abundance of PLFA 18:2v6 was reportedly found in organically managed soils compared with those of conventional management (Yeates et al., 1997). In this study a higher number of fungal plate counts were recovered in ungrazed soils, and inorganic N fertiliser had no effect on colony numbers, whilst, a previous study (Grayston et al., 2001) reported higher numbers of culturable fungi in unimproved soils. Additionally, no effects of inorganic N or soil drainage were found on the amounts of fungal PLFA 18:2v6 recovered from soils at the same experimental site as this study (Clegg et al., 2003). Conversely, using active hyphal lengths as an indicator of fungal biomass, a positive correlation with the addition of N fertiliser to soils has been reported (Klein and Paschke, 2000). The physical disturbance of the soil through tillage has been shown to have a negative effect on hyphal length (Klein and Paschke, 2000; Frey et al., 1999). Data obtained for the actinomycetes indicated that management impacted on the abundance and community composition. The abundance of the actinomycete PLFA 10Me18:0 was greatest in the grazed and unfertilised treatment, and the PCR–DGGE molecular profiles also indicated that inorganic N fertiliser impacted on the community composition. In a previous study on different soils at the same experimental site, the abundance of PLFA 10Me18:0 was found to be greatest in unfertilised soils and community composition of actinomycetes was effected by both soil drainage and inorganic N fertiliser (Clegg et al., 2003). In addition to the aforementioned factors, previous studies have also reported that abundance of PLFA 10Me18:0 was also sensitive to changes in soil depth (Fritze et al., 2000) and liming (Frostega˚rd et al., 1993), and it appears that abundance of the actinomycete PLFA10Me18:0 is an indicator of change in soil conditions.
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
In summary, the findings of this study provide evidence that both cattle grazing and inorganic N fertiliser additions impact on the microbial composition of soils. Previous studies had reported changes in the production rates of CO2–N2O–NO2 emissions, Nmineralisation and microbial biomass, however, it was unclear from those studies whether differences in transformation rates where due to changes in the activities of micro-organisms or shifts in community composition. The results of this study demonstrated that management regime does impact on the general microbial community composition and now the focus of future studies is to make that specific mechanistic link between soil process and microbial species.
Acknowledgements The Institute of Grassland and Environmental Research is supported by the Biotechnology and Biological Sciences Research Council.
References Antil, R.S., Lovell, R.D., Hatch, D.J., Jarvis, S.C., 2001. Mineralisation of nitrogen in permanent pastures amended with fertilizer or dung. Biol. Fertil. Soil 33, 132–1388. Ba˚a˚th, E., Anderson, T.-H., 2003. Comparison of soil fungal/bacterial ratios in a pH gradient using physiological and PLFA-based techniques. Soil Biol. Biochem. 35, 955–963. ˚ ., 1996. Changes in soil Bardgett, R.D., Hobbs, P.J., Frostega˚rd, A fungal:bacterial biomass ratios following reductions in the intensity of management of an upland grassland. Biol. Fertil. Soils 22, 261–264. Bardgett, R.D., Leemans, D.K., Cook, R., Hobbs, P.J., 1997. Seasonality of the soil biota of grazed and ungrazed hill grasslands. Soil Biol. Biochem. 29, 1285–1294. Bligh, E.G., Dyer, W.J., 1959. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917. Cavigelli, M.A., Robertson, G.P., Klug, M.J., 1995. Fatty acid methyl ester (FAME) profiles as measures of soil microbial community structure. Plant Soil 170, 99–113. Clayton, S.J., Clegg, C.D., Murray, P.J., Gregory, P.J., 2005. Determination of the impact of continuous defoliation of Lolium perenne and Trifolium repens on bacterial and fungal community structure in rhizosphere soil. Biol. Fertil. Soil 41, 109–115. Clegg, C.D., Lovell, R.D.L., Hobbs, P.J., 2003. The impact of grassland management regime on the community structure of selected bacterial groups in soils. FEMS Microbiol. Ecol. 43, 263–270.
81
Clegg, C.D., Ritz, K., Griffiths, B.S., 2000. %G + C profiling and cross hybridisation of microbial DNA reveals great variation in below-ground community structure in UK upland grasslands. Appl. Soil Ecol. 14, 125–134. DEFRA, 2002. The Environment in Your Pocket. Department for Environment and Rural Affairs, London. Federle, T.W., 1986. Microbial distribution in soil: new techniques. In: Megusar, F., Gantar, M. (Eds.), Perspectives in Microbial Ecology. Slovene Society for Microbiology, Ljubljana, Slovenia, pp. 493–498. Frey, S.D., Elliot, E.T., Paustian, K., 1999. Bacterial and fungal abundance and biomass in conventional and no-tillage agroecosystems along two climatic gradients. Soil Biol. Biochem. 31, 573–585. Fritze, H., Pietika¨inen, J., Pennanen, T., 2000. Distribution of microbial biomass and phospholipid fatty acids in podzol profiles under coniferous forest. Eur. J. Soil Sci. 51, 565–573. ˚ ., Ba˚a˚th, E., Tunlid, A., 1993. Shifts in the structure of Frostega˚rd, A soil microbial communities in limed forests as revealed by phospholipid fatty acid analysis. Soil Biol. Biochem. 25, 723–730. Garland, J.L., Mills, A.L., 1991. Classification and characterisation of heterogenous microbial communities on the basis of patterns of community-level sole-carbon source utilisation. Appl. Environ. Microbiol. 57, 2351–2359. Gill, K., Jarvis, S.C., Hatch, D.J., 1995. Mineralization of nitrogen in long-term pasture soils: effects of management. Plant Soil 172, 153–162. Gordon, I.J., Duncan, P., 1993. Objectives for production and conservation in grasslands: effect of large grazing ungulates. In: Haggar, R.J., Peel, S. (Eds.), Grassland Management and Nature Conservation, Occasional Symposium No. 28, British Grassland Society. Gray, N.D., Hastings, R.C., Sheppard, S.K., Loughnane, P., Lloyd, D., McCarthy, A.J., Head, I.M., 2003. Effects of soil improvement treatments on bacterial community structure and soil processes in an upland grassland soil. FEMS Microbiol. Ecol. 46, 11–22. Grayston, S.J., Griffith, G.S., Mawdsley, J.L., Campbell, C.D., Bardgett, R.D., 2001. Accounting for variability in soil microbial communities of temperate upland grassland ecosystems. Soil Biol. Biochem. 33, 533–351. Hatch, D.J., Lovell, R.D., Antil, R.S., Jarvis, S.C., Owen, P.M., 2000. Nitrogen mineralization and microbial activity in permanent pastures amended with nitrogen fertilizer or dung. Biol. Fertil. Soil 30, 288–293. Hatch, D.J., Sprosen, M.S., Jarvis, S.C., Ledgard, S.F., 2002. Use of labelled nitrogen to measure gross and net rates of mineralization and microbial activity in permanent pastures following fertilizer applications at different time intervals. Rapid Commun. Mass Spectrom. 16, 2172–2178. Heuer, H., Kresk, M., Baker, P., Smalla, K., Wellington, E.M.H., 1997. Analysis of actinomycete communities by specific amplification of genes encoding 16S rRNA and gel-electrophoretic separation in denaturing gradients. Appl. Environ. Microbiol. 63, 3233–3241. Holland, J.N., 1995. Effects of above ground herbivory on soil microbial biomass in conventional and no-tillage agroecosystems. Appl. Soil Ecol. 2, 275–279.
82
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
Hopkins, A., Hopkins, J.J., 1993. UK grasslands now: agricultural production and nature conservation. In: Haggar, R.J., Peel, S. (Eds.), Grassland Management and Nature Conservation, Occasional Symposium No. 28, British Grassland Society. Kennedy, N., Brodie, E., Connolly, J., Clipson, N., 2004. Impact of lime, nitrogen and plant species on bacterial community structure in grassland microcosms. Environ. Microbiol. 6, 1070– 1080. Klein, D.A., Paschke, M.W., 2000. A soil microbial community structural-functional index: the microscopy-based total/active/ active fungal/bacterial (TA/AFB) biovolumes ratio. Appl. Soil Ecol. 14, 257–268. Lichtenstein, C., Draper, J., 1985. Genetic engineering of plants. In: Glover, D.M. (Ed.), DNA Cloning, vol. 2. IRL Press, Oxford, pp. 67–120. Lovell, R.D., Hatch, D.J., 1998. Stimulation of microbial activity following spring applications of nitrogen. Biol. Fertil. Soils 26, 28–30. Lovell, R.D., Jarvis, S.C., 1996a. Effects of urine on soil microbial biomass, methanogenesis, nitrification and denitrification in grassland soils. Plant Soil 186, 265–273. Lovell, R.D., Jarvis, S.C., 1996b. Effect of cattle dung on soil microbial biomass C and N in a permanent pasture soil. Soil Biol. Biochem. 28, 291–299. Lovell, R.D., Jarvis, S.C., Bardgett, R.D., 1995. Soil microbial biomass and activity in long-term grassland: effects of management changes. Soil Biol. Biochem. 27, 969–975. MacDuff, J.H., Jackson, S.B., 1992. Influx and efflux of nitrate and ammonium in Italian ryegrass and white clover roots: comparisons between effects of darkness and defoliation. J. Exp. Bot. 43, 525–535. Mawdsley, J.L., Bardgett, R.D., 1997. Continuous defoliation of perennial ryegrass (Lolium perenne) and white clover (Trifolium repens) and associated changes in the composition and activity of the microbial population of an upland grassland soil. Biol. Fertil. Soil 24, 52–58. Mikola, J., Yeates, G.W., Wardle, D.A., Barker, G.M., Boner, K.I., 2001. Response of soil food-web structure to defoliation of different plant species combinations in an experimental grassland community. Soil Biol. Biochem. 33, 205–214. Muyzer, G., De Waal, E.C., Uitterlinden, A.G., 1993. Profiling of complex microbial populations by denaturing gradient gel elec-
trophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59, 695–700. Parkin, T.B., Starr, J.L., Meisinger, J.J., 1987. Influence of sample size on measurement of soil denitrification. Soil Sci. Soc. Am. J. 51, 1492–1501. Paterson, P., Sim, A., 1999. Rhizodeposition and C-partitioning of Lolium perenne in axenic culture affected by nitrogen supply and defoliation. Plant Soil 216, 155–164. Ritz, K., McNicol, J.W., Nunan, N., Grayston, S., Millard, P., Atkinson, D., Gollotte, A., Habeshaw, D., Boag, B., Clegg, C.D., Griffiths, B.S., Wheatley, R.E., Glover, L.A., McCaig, A.E., Prosser, J.I., 2004. Spatial structure in soil chemical and microbiological properties in an upland grassland. FEMS Microbiol. Ecol. 49, 191–205. Tallowin, J.R.B., 1996. Effects of inorganic fertilisers on flower-rich hay meadows: a review using a case study on the Somerset Levels, UK. Grassland Forage Abstr. 66, 147–152. van Elsas, J.D., Duarte, G.F., Keijzer-Wolters, A., Smit, E., 2000. Analysis of the dynamics of fungal communities in soil via fungal specific PCR of soil DNA followed by denaturing gradient gel electrophoresis. J. Microbiol. Methods 43, 133–151. Vinten, A.J.A., Lewis, D.R., Fenlon, D.R., Leach, K.A., Howard, R., Svoboda, I., Ogden, I., 2002. Fate of Escherichia coli and Escherichia coli 0157 in soils and drainage water following cattle slurry application at 3 sites in southern Scotland. Soil Use Manage. 18, 223–231. Vinten, A.J.A., Douglas, J.T., Lewis, D.R., Aitken, M.N., Fenlon, D.R., 2004. Relative risk of surface water pollution by E. coli derived from faeces of grazing animals compared to slurry application. Soil Use Manage. 20, 13–22. White, S.L., Sheffield, R.E., Washburn, S.P., King, L.D., Green, J.T., 2001. Spatial and time distribution of dairy cattle excreta in an intensive pasture system. J. Environ. Qual. 30, 2180–2187. 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. Yeates, G.W., Bardgett, R.D., Cook, R., Hobbs, P.J., Bowling, P.J., Potter, J.F., 1997. Faunal and microbial diversity in three welsh grassland soils under conventional and organic management regimes. J. Appl. Ecol. 34, 453–470.
Impact of cattle grazing and inorganic fertiliser additions to managed grasslands on the microbial community composition of soils Christopher D. Clegg * Institute of Grassland and Environmental Research, North Wyke, Okehampton, Devon EX20 2SB, UK Received 25 October 2004; received in revised form 10 April 2005; accepted 12 April 2005
Abstract A study was undertaken to determine if cattle grazing on managed grasslands had an impact on the microbial community composition of soils. Microbial community molecular profiles of bacteria, actinomycetes, pseudomonads and fungi were generated by polymerase chain reaction (PCR) amplification of rDNA sequences from community DNA isolated from soils. PCR products were profiled using denaturing gradient gel electrophoresis (DGGE) and analysed by principal co-ordinate analysis. PCR–DGGE profiles indicated that cattle grazing had an impact on the pseudomonad community structure only, and that the addition of inorganic nitrogen (N) fertiliser impacted on bacterial, actinomycete and pseudomonad community structure. There was no difference in the community profiles of fungi from grazed and N fertilised grassland plots. Analysis of phospholipid fatty acid (PLFA) profiles revealed that both cattle grazing and N fertiliser impacted on microbial community structure. The abundance of individual PLFAs differed between treatments, with bacterial (15:0), actinomycete (10Me18:0) and fungal (18:2v6) PLFAs not affected directly by grazing cattle and N fertiliser, however, there were significant grazing–fertiliser interactions. Bacterial plate counts were highest in the N fertilised plots and fungal plate counts were highest in the cattle grazed plots. Analysis of molecular microbial community profiles with PLFA and background soil data revealed several significant correlations. Notably, soil pH was positively correlated with PCO1 of the pseudomonad community profiles and negatively correlated with the fungal PLFA 18:2v6. Fungal DGGE profiles were negatively correlated with the fungal PLFA 18:2v6, and bacterial and fungal plate counts positively correlated with each other. Correlation analysis using PC1 from PLFA profile data showed no significant relationship with soil organic matter, pH, total C and total N. The results indicate that cattle grazing and N fertiliser addition to grasslands impact on the community composition of specific groups of micro-organisms. The consequences of such changes in population structure may have implications regarding the dynamics of nutrient turnover in soils. # 2005 Elsevier B.V. All rights reserved. Keywords: Grazing; Grasslands; Micro-organsims; Molecular profiling; Bacteria; Fungi
1. Introduction * Tel.: +44 1837 883532; fax: +44 1837 82139. E-mail address: [email protected].
Micro-organisms play a key role in grassland ecosystems through regulating the dynamics of
0929-1393/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2005.04.003
74
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
organic matter decomposition and plant nutrient availability. Whilst there is considerable information available concerning the impact of both animal grazing and inorganic fertiliser application on communities of macro-fauna and flora, the effects on microbial community composition in soils have received little attention. Previous studies have tended to focus on the effects of cattle urine and faeces on soil processes, e.g. nitrification, denitrification, soil respiration, microbial biomass (e.g. Lovell and Jarvis, 1996a,b; Hatch et al., 2000), and issues related to potential pathogen movement in soils (e.g. Vinten et al., 2002), however, little seems to be known about the impact of above ground animal grazing on the microbial community composition of agricultural grassland soils. There is clearly a need to further our understanding of the microbiology of grassland soils given that in the U.K., about 50% (Gordon and Duncan, 1993) of the land area comprises agricultural grassland and 35% of the land area is grazed (DEFRA, 2002). In order to maintain the productivity of these grasslands, inorganic nitrogen (N) fertiliser is applied to about 85% of agricultural grasslands in the U.K. (Hopkins and Hopkins, 1993) to meet the demands of grazing animals. One of the reasons for the paucity of microbiological studies on grazed grasslands may be that studies were traditionally limited by the resolution of the available methodologies. One of the problems associated with the study of soil microbiology was that most bacteria, and an unknown proportion of fungi, could not be readily isolated which thus impaired our understanding of community composition. However, microbial community based methodologies such as DNA and PLFA profiling approaches can now circumvent the problems associated with culturing. Advances in molecular community profiling approaches can provide information regarding the community composition of microbial populations in soils, for example, through the isolation of microbial DNA from soil, community profiles for bacteria (Muyzer et al., 1993) and fungi (van Elsas et al., 2000) can be generated through the PCR amplification of 16S and 18S rRNA genes, respectively, and molecular community profiles compared through DGGE. The objective of this study was to determine if cattle grazing and N fertiliser application to managed grasslands had an impact on the microbial community
composition of the soils. This was undertaken through molecular profiling of the eubacterial, actinomycete, pseudomonad and fungal communities of these soils together with PLFA profiling and the determination of some soil background characteristics.
2. Materials and methods 2.1. Soils Soils were sampled from the Rowden long-term experimental site at the Institute of Grassland and Environmental Research (IGER), North Wyke Research Station, Devon in SW England (NGR SX 650 995). These swards had been under long-term pasture for the previous 50 years and under the current management regimes for the past 15 years. The treatments analysed in this study where cattle grazing and inorganic N fertiliser in the following combinations: ungrazed and unfertilised (UG–O), grazed and unfertilised (G–O), grazed and fertilised at 280 kg inorganic N (ha yr)1 (G–N), and ungrazed and fertilised at 280 kg inorganic N (ha yr)1 (UG–N). The stocking density for cattle was four steers ha1 and was managed accordingly to maintain a sward height of about 7.5 cm. The grass in the ungrazed plots was cut and removed three times during the growing season. The soil is a poorly drained silty clay loam of the Hallsworth series. Soil samples were taken as follows: about 10–12 mm 25 mm 50 mm deep cores were taken from each of random triplicate quadrats within a single ha1 plot of each of the four different management treatments. Soils were sieved through a 4 mm mesh sieve. Total C and total N contents were obtained with an automated Dumas procedure on a Carlo Erba NA2000 elemental analyser (CE Instruments) and soil pH (water), organic matter content (loss of weight on ignition) and bulk density were also determined (Lovell et al., 1995). 2.2. Bacterial and fungal plate counts Numbers of culturable bacteria and fungi were determined by plating samples onto solid media. About 0.5 g (fresh wt.) of each replicate soil sample was added to 1.8 ml 0.1% sodium pyrophosphate in an Eppendorf tube and mixed by vortexing. Ten-fold
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
serial dilutions were made in sterile 0.1% sodium pyrophosphate and 100 ml aliquots of diluted soil suspension were spread-plated onto 10% tryptone soya agar (0.1 TSA) to determine bacterial plate counts. To determine fungal plate counts, 100 ml aliquots of the soil serial dilutions were spread-plated onto potato dextrose agar (PDA) containing streptomycin (50 mg ml1) to suppress bacterial growth. Agar plates were maintained at 15–17 8C for 5 days before counting numbers of colony forming units (cfu). 2.3. Isolation of total DNA from soils To about 1.0 g (fresh weight) soil was added 1.0 g 0.1 mm diam. zirconia/silica beads (BioSpec. Products Inc.) and 400 ml guanidinium thiocyanate solution (4 M guanidinium thiocyanate, 0.5% sarkosyl, 0.25 M sodium citrate, pH 7.0). Samples were then processed in a Mini-beadbeater (Biospec Products Inc.) at 5000 rpm for 60 s and the soil suspension centrifuged at 13,000 rpm (MSE Micro Centaur, U.K.) for 1 min. The supernatant was mixed with an equal volume of phenol (pH 8.0) and centrifuged at 13,000 rpm for 5 min. The upper aqueous phase was mixed with an equal volume of chloroform and centrifuged at 13,000 rpm for 5 min. To precipitate out nucleic acids, 0.1 vol of 5 M NaCl and 2.5 vol of 100% ethanol were added to the aqueous phase and centrifuged at 13,000 rpm for 30 min. The resultant pellet was then washed twice in 70% ethanol and dried. The dried pellet was resuspended in sterile distilled water. The amounts of DNA isolated from the different soils were determined colorimetrically by reaction with diphenylamine (Lichtenstein and Draper, 1985). 2.4. PCR amplification of 16S and 18S rDNA PCR amplification was carried out to generate products for molecular population profiling of the bacterial, actinomycete and fungal communities. For profiling the bacterial communities, PCR products were generated using total community DNA as the template for amplification of partial 16S rRNA gene sequences. To generate molecular profiles of the actinomycete and fungal community structure a nested PCR approach was adopted, whereby the first
75
round of PCR used total community DNA as the template, and then the second round of PCR used the products from the first round of the nested PCR as the template. All PCR amplifications were carried out in a 40 ml reaction volume containing 20 pmol of each primer, 250 mM dNTPs, 3 U Expand High Fidelity polymerase (Roche Diagnostics, U.K.), 4 ml 10 reaction buffer. For the amplification of 16S rRNA genes and the first round of nested PCR for the actinomycete and fungal community profiles, about 50 ng of total community DNA isolated from soil was used as the template for amplification and each reaction also contained 16 mg bovine serum albumin (Roche Diagnostics, U.K.). PCR amplification of the 16S rRNA eubacterial genes was carried out using the primers 341f-GC and 534r (Muyzer et al., 1993). The GC clamp (CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG) was attached to the 50 -end of the forward primer. PCR was performed using the following cycle, 95 8C for 5 min followed by 35 cycles of 95 8C for 1 min, 55 8C for 1 min, 72 8C for 2 min. A final extension time of 10 min at 72 8C was included. For the actinomycetes, the primers F243 and R1378 (Heuer et al., 1997) were used in conjunction with the following cycle of 95 8C for 5 min followed by 35 cycles of 95 8C for 1 min, 63 8C for 1min, 72 8C for 2 min. This was followed by a final extension time of 10 min at 72 8C. The products from the first round of PCR were then run on a 1% low melting point agarose gel (Roche Diagnostics), stained in ethidium bromide and visualised under ultraviolet light. Bands of the estimated product sizes were excised from the gel, melted at 70 8C and 1 ml was added to the reaction mix for the second round of PCR using the primers 341f-GC and 534r. The cycle used for the second round of PCR was the same as that described earlier for the eubacterial primers. To generate PCR products for fungal community profiling, the first round of nested PCR used the primer pair EF4 and Fung5r (van Elsas et al., 2000) with the following thermal cycle, 95 8C for 5 min, 40 cycles of 95 8C for 1 min, 48 8C for 1 min, 72 8C for 2 min and a final extension at 72 8C for 5 min. The second round of nested PCR used 0.2 ml of the products from the first round of nested PCR as the target sequence with primers NS2f and Fungi5rGC (van Elsas et al., 2000) using the following cycle, 95 8C for 5 min, 30 cycles at 95 8C for 1 min, 55 8C for 30 s, 72 8C for 1 min and a
76
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
final extension of 72 8C for 5 min. All PCR samples were amplified with a Primus Thermocycler (MWGBiotech, U.K.) and final PCR products were checked on a 1.2% agarose gel stained with ethidium bromide.
an indicator of fungal biomass (Federle, 1986). Other PLFAs determined were i14:0, 14:0, 16:0, 16:1v7, 17:1v6, nMe18:0, 18:0, trans18:1v9 and 20:0. 2.7. Banding pattern analysis and statistics
2.5. Molecular profiling of soil bacterial and fungal population structure PCR products were resolved using DGGE to provide molecular profiles of bacterial and fungal communities. For the generation of bacterial community profiles, polyacrylamide gels (8% acrylamide, 0.5 TAE, 37:1 acrylamide:bisacrylamide) were cast using 40–55% denaturant (100% denaturant was defined as 7 M urea with 40% [vol/vol] formamide). For the fungal community structure profiles, a denaturant range of 45–55% was used. PCR products were loaded into the lanes of the gel in a random order to avoid any potential bias in the later analysis. The gel was run using a DCode system (Bio-Rad Laboratories) at a constant temperature of 60 8C and at 60 V for 16 h. After electrophoresis, gels were fixed for at least 2 h in a solution of 10% ethanol and 0.5% acetic acid. The gels were then stained in a solution of 0.1% (wt/ vol) silver nitrate for 20 min before briefly rinsing and developing (0.02 g NaBH4, 0.8 ml formaldehyde, 200 ml 1.5% [wt/vol] NaOH) until the bands appeared. Gels were then fixed in 0.75% Na2CO3 for 10 min before scanning with a Hewlett Packard Scanjet 5370C. Banding patterns were determined using Phoretix 1D Gel Analysis Software, Version 4.0 (Phoretix International, Newcastle Upon Tyne, U.K.).
Similarity indices of PCR–DGGE molecular profiles for bacterial and fungal communities were determined using binary data only. Similarity matrices were generated from binary data for each lane using the Jaccard coefficient as previously described (Clegg et al., 2003). The similarity indices were used in principal co-ordinate analysis (PCO) and the first 6 PCOs (typically accounting for about 70–80% of the variability) were then analysed by two-way MANOVA (multivariate analysis of variance, Genstat fifth edition) to determine statistical differences in the bacterial and fungal community profiles. For the analysis of PLFA data, the amounts (nmol g1 dry soil) were log transformed and analysed initially by principal component (PC) analysis to reduce the dimensionality. The first three principal components (accounting for 96.6% of the variability) were analysed by two-way MANOVA to determine treatment effects on the PLFA composition of the soils. Two-way analysis of variance was also used to determine treatment related effects on amounts of individual PLFAs isolated from different plots. Correlation analyses were conducted on PCOs 1 and 2 and PCs 1 and 2 with individual PLFAs, plate counts and background soil data. Results were considered significant at P 0.05.
2.6. Phospholipid fatty acid analysis 3. Results PLFAs were extracted, fractionated and quantified from replicate 2 g soil samples and analysed as previously described (Clegg et al., 2003) using the method of Bardgett et al. (1996), which is based on the method of Bligh and Dyer (1959). Fatty acid methyl esters were identified by chromatographic retention time and compared to a standard qualitative mix (Supelco UK, Poole, Dorset, UK). Fatty acid nomenclature was as follows: fatty acids i15:0, a15:0, 15:0, i16:0, 17:0, i17:0, cy17:0, cis18:1v7 and cy19:0 represented current known bacterial PLFAs (Frostega˚rd et al., 1993), 10Me18:0 was indicative of actinomycetes and 18:2v6 was used as
Cattle grazing and fertiliser N application had some impact on the background soil characteristics (Table 1). Total carbon (% content) was significantly greatest in the grazed plots (P = 0.03), and whilst, % organic matter was also highest in the grazed plots, this was not significantly greater than ungrazed plots. Neither grazing nor fertiliser N had an effect on the total N (%) content of the soils, however, those soils that received fertiliser did have significantly lower pH values (P = 0.03). Bacterial plate counts were significantly higher (P = 0.02) in the fertilised soils than the unfertilised
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
77
Table 1 Means (standard errors) of background soil characteristics (n = 3) Treatment
Soil pH
Organic matter (%)
Total carbon (%)
Total nitrogen (%)
Grazed N Grazed + N Ungrazed N Ungrazed + N
5.85 5.72 6.02 5.43
14.0 14.2 12.9 13.7
6.65 7.32 5.91 6.43
0.66 0.71 0.63 0.66
(0.10) (0.11) (0.09) (0.19)
(1.12) (0.43) (0.76) (0.29)
(0.41) (0.34) (0.23) (0.24)
(0.03) (0.06) (0.03) (0.02)
N: unfertilised; +N: fertilised with inorganic nitrogen.
soils, and grazing was not a significant factor. In the fertilised soils, mean bacterial plate counts (per gram dry soil) were 2.09 107 and 2.56 107 in the grazed and ungrazed treatments and 1.11 107 and 0.94 107 for the unfertilised grazed and ungrazed treatments. Fungal plate counts were significantly higher (P = 0.05) in the ungrazed soils, whilst, fertiliser effect was not significant. Mean colony forming units (per gram dry soils) for the ungrazed soils were 4.26 105 (fertilised) and 1.8 105 (unfertilised) and in the grazed soils mean numbers of cfus were 0.93 105 (fertilised) and 1.36 105 (unfertilised). Bacterial and fungal plate counts were significantly positively correlated. Total microbial DNA was readily isolated from all soils with amounts varying from about 59 to 115 mg g1 soil. Amounts of DNA isolated from soils were not influenced by either grazing or inorganic N fertiliser. All DNA samples were readily amplified by PCR and molecular profiles for eubacteria, actinomycete, pseudomonad and fungal communities generated. Many of the banding patterns were complex and variable between replicates. Statistical analysis was conducted on the first 6 PCOs, and for the purpose of illustration, the relative community structures are represented by the ordination plots in Fig. 1, where PCOs 1 and 2 typically represent 14–19 and 13–15% of the variation. The total numbers of different banding positions between gel lanes analysed were 132 bands for the eubacterial profiles, 117 actinomycete bands, 94 pseudomonad bands and 69 different fungal bands. MANOVA of the first 6 PCOs revealed that cattle grazing had an impact on the pseudomonad community structure (P = 0.01) only. However, ANOVA of the individual PCOs also revealed that cattle grazing was the discriminant in PCO2 of the actinomycete community profiles (P = 0.02). MANOVA of the first 6 PCOs indicated that inorganic N fertiliser impacted on the community
structures of the eubacteria (P = 0.002), actinomycetes (P = 0.05) and pseudomonads (P = 0.02) but not the fungi. There was also a significant grazing– inorganic N interaction for the pseudomonad community structure (P = 0.02). The amounts of PLFAs isolated from soils varied considerably, from about 50–400 nmol g1 dry soil, however, these amounts were not influenced by either cattle grazing or inorganic N fertiliser. For all PLFAs combined, MANOVA of the first 6 PCOs (92% variation) indicated that cattle grazing (P = 0.02), inorganic N fertiliser (P = 0.006) and the interaction (P = 0.008) had significant effects on the overall community profiles (Fig. 2). The Gram positive bacterial PLFA i17:0 was significantly higher in both grazed and fertilised soils, and amounts of those PLFAs indicative of the actinomycetes (10Me18:0) and fungi (18:2v6) were not affected by both cattle grazing and inorganic nitrogen fertiliser alone. There were significant grazing–fertiliser interactions on the PLFAs 14:0, 15:0, i16:0, 16:0, 16:1v7, 17:0, i17v6, 10Me18:0, 18:0, 18:2v6, 20:0. Analysis of PLFA loadings from the principal component analysis indicated that PLFAs i15:0, trans18:1v9 and i17:0 were outliers responsible for some of the determined differences due to different treatments. PLFA i15:0 is indicative of Gram positive bacteria and amounts were only significantly higher in the grazed unfertilised soils. Trans18:1v9 is indicative of Gram negative bacteria and was also highest in grazed and unfertilised soils. Correlation analysis was also undertaken using the first two principal co-ordinates from the PCR–DGGE and PLFA profiles. PCR–DGGE PCOs 1 and 2 typically accounted for 14–18 and 12–14% of the variability, respectively, whilst, PLFA PC1 and PC2 accounted for 73.1 and 14.7%, respectively. Significant positive correlations were obtained between eubacterial PCO1 and bacterial plate counts
78
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
Fig. 1. (a–d) Plots of PCO1 and PCO2 means (standard error) produced from the multivariate analysis of (a) eubacterial, (b) actinomycete, (c) pseudomonad and (d) fungal PCR–DGGE banding profiles from ungrazed–unfertilised (*), grazed–unfertilised (*), ungrazed–N fertilised (~) and grazed–N fertilised (~) grassland soils.
(P = 0.035), pseudomonad PCO1 with soil pH (P = 0.017) and for actinomycete PCO1 with PLFA i15:0 (P = 0.04). Significant negative correlations were obtained between actinomycete PCO1 and PLFA i17:0 (P = 0.02), pseudomonad PCO2 and both PLFA i15:0 (P = 0.043) and fungal plate counts (P = 0.047),
fungal PCO1 and fungal PLFA 18:2v6 (P = 0.035), and PLFA PC2 and bacterial plate counts (P = 0.031). Correlation analysis of PLFA PC1 and soil characteristics revealed that there were no significant associations between PC1 and soil organic matter, pH, total N, total C, bacterial and fungal plate counts. Total soil C was significantly positively correlated with PLFA i17:0 (P = 0.025), DNA (P = 0.034), organic matter (P = 0.004), and total N was significantly positively correlated with DNA (P = 0.003) and organic matter (P = 0.005). Soil pH was significantly negatively correlated with the fungal PLFA 18:2v6 (P = 0.01).
4. Discussion
Fig. 2. Plot of PC1 and PC2 means (standard error) produced from the multivariate analysis of PLFA profiles obtained from ungrazed– unfertilised (*), grazed–unfertilised (*), ungrazed–N fertilised (~) and grazed–N fertilised (~) grassland soils.
The main finding of this study was that both cattle grazing and inorganic N application to grasslands impacted on the community composition of microbial populations in managed soils. These results provide some evidence to part explain those previous studies reporting changes in transformation processes due to
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
cattle urine and faeces application to soils (e.g. Lovell and Jarvis, 1996a,b; Hatch et al., 2000). Grazing livestock can play an important role in the microbial ecology of grasslands through a series of specific factors associated with the presence of cattle. The management factors considered in this study were cattle grazing and inorganic N fertiliser application, however, in reality each of these events is a composite of several more specific, and possibly interactive, factors. For example, the practice of grazing cattle is a complex event and could comprise a range of specific factors such as faecal and urine deposition, shifts in rhizosphere exudation patterns resulting from defoliation effects of cattle grazing, shifts in botanical composition due to grazing and changes in soil structure and aerobicity due to animal compaction and poaching. Animal faeces and urine contain readily utilisable substrates and inputs into grasslands can result in changes in microbial activities. Inputs of cattle urine to soils have been reported to result in increases in respiration, N2O and NO2 emissions and an increase in microbial biomass (Lovell and Jarvis, 1996a). Within a grazed area, there are any number of urine patches of variable ages with differing amounts of mineral N present in the soil. In a previous study in an upland grassland soil, Ritz et al. (2004) reported a consistent trend of higher concentration notional urine patches with greater values of other soil chemical properties, microbial biomass and the abundance of many microbial PLFAs. The addition of synthetic sheep urine to soils was reported to immediately stimulate an increase of bacterial numbers, however, there were no effects on pseudomonad, fungal and yeast plate counts (Williams et al., 2000). The application of synthetic urine had a delayed effect on the utilisation of specific substrates, with activity greatest during the period 2–5 weeks after its addition to soil, indicating the contribution of urine to the patchiness of microbial activities and population composition in grazed grasslands. Cattle faeces contain soluble C, as well as small amounts of N and can stimulate increases in soil respiration and mineralisation processes (Hatch et al., 2000). An important point to consider when assessing the effect of the presence of animals on the microbiological quality of soils is that animal faeces deposited on the surface of the grazed paddock also contains a large concentration of micro-organisms.
79
Interpretation of results may become difficult, depending on the target group of micro-organisms because of difficulties discriminating those microbes in the soils, which are affected by the faecal deposit, and those that are merely introduced to the soil from within the faeces. Urine and faecal deposits from cattle may constitute between 3% (Antil et al., 2001) and 10% (White et al., 2001) of the surface area of a grazed grassland each year, however, up to about 14% of the daily faecal input from grazing animals can be washed away into watercourses during a rainfall event (Vinten et al., 2004). Whilst, it is difficult to assess the contribution of faecally introduced micro-organisms to the soil microbial community composition, their presence is inherent to grazing management. Taking into consideration the effects of rainfall on faeces through dissipation, dilution and run-off from fields, and the generally poor survival of faecally derived micro-organisms in soils, it is considered that in the context of this study the faecally introduced microorganisms contributed a minor unknown proportion of the soil microbial community composition detected. A feature of this study was the amount of variation between replicates in the PCR–DGGE banding patterns and PLFA analyses. Spatial variation is synonymous with field based studies and has previously been reported in phenotypic determinations on microbial communities such as metabolic (Garland and Mills, 1991) and fatty acid methyl ester profiling (Cavigelli et al., 1995), and also process based determinations (Parkin et al., 1987). In addition to phenotypic variation in soils, there is also some emerging evidence regarding the spatial composition of microbial communities based on DNA molecular studies at different scales. For example, using a broadscale molecular approach (Clegg et al., 2000), variation in the composition of microbial community DNA between replicate soil samples was sometimes found to be as great as the variation between treatment effects in upland grasslands, and that to a certain degree this may have obscured some treatment related effects. More recently, spatial heterogeneity has been reported to occur at the centimetre scale in upland grassland soils (Ritz et al., 2004) and also between different root regions of the same plant species (Clayton et al., 2005). The reasons for variability between replicate samples in this study are not clear,
80
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
however, in consideration of the findings of other studies it is likely that they are complex and attributable to many different factors within the soil environment. A reduction in botanical diversity (e.g. Tallowin, 1996) and shifts in the rates of some soil processes (e.g. Gill et al., 1995; Hatch et al., 2002; Lovell and Hatch, 1998) through the application of inorganic N fertiliser have previously been recognised, however, there is also emerging recent evidence that shifts in soil microbial community composition may also occur as a result of fertiliser amendment (Clegg et al., 2003; Gray et al., 2003; Kennedy et al., 2004). The mechanisms through which inorganic N fertiliser support changes in microbial community composition are not clear, and some may be interactive. Microbial community composition can be controlled by soil pH (Ba˚a˚th and Anderson, 2003), and whilst, many grassland soils are limed occasionally to counter the acidifying effects of inorganic N application, it is possible that localised pH changes occur in the soils as a result of fertiliser amendment. Changes in the botanical composition of grasslands through fertiliser N addition may indirectly impact on microbial community composition through the shift in the C quality and quantity of the plant material entering the soil. Also, the addition of inorganic N to soil may drive changes in the microbial community composition through direct competition of microbes for N as a substrate for growth or respiration purposes. The effects of defoliation through above ground herbivory of plants by cattle may also have an impact on the dynamics of microbial community structure and nutrient cycling within the rhizosphere through changes in the C balance. Defoliation can lead to increased losses of C (Paterson and Sim, 1999) and N (MacDuff and Jackson, 1992), and as a consequence, increases in microbial biomass (Holland, 1995; Mawdsley and Bardgett, 1997) and culturable bacteria (Mawdsley and Bardgett, 1997) in the rhizosphere of defoliated plants. Conversely, it has also been reported that defoliation can have no impact on microbial biomass (Mikola et al., 2001). The results of this study, and comparisons with others, suggest that the impact of agricultural management on the fungal communities in soils is unclear. In this present study, the abundance of the fungal PLFA 18:2v6 was not found to be influenced
by cattle grazing and N alone, however, there was a significant negative correlation with soil pH (higher abundance at lower pH), which was possibly a reflection of the slightly acidic pH optima for fungal activity generally. Interestingly, Bardgett et al. (1997) reported that the amount of fungal PLFA 18:2v6 was reduced when sheep were removed from an upland grassland and this was attributed to the concurrent cessation of liming and removal of readily utilisable inputs in the form of sheep excreta and urine and changes in the quality of plant root exudates. A greater abundance of PLFA 18:2v6 was reportedly found in organically managed soils compared with those of conventional management (Yeates et al., 1997). In this study a higher number of fungal plate counts were recovered in ungrazed soils, and inorganic N fertiliser had no effect on colony numbers, whilst, a previous study (Grayston et al., 2001) reported higher numbers of culturable fungi in unimproved soils. Additionally, no effects of inorganic N or soil drainage were found on the amounts of fungal PLFA 18:2v6 recovered from soils at the same experimental site as this study (Clegg et al., 2003). Conversely, using active hyphal lengths as an indicator of fungal biomass, a positive correlation with the addition of N fertiliser to soils has been reported (Klein and Paschke, 2000). The physical disturbance of the soil through tillage has been shown to have a negative effect on hyphal length (Klein and Paschke, 2000; Frey et al., 1999). Data obtained for the actinomycetes indicated that management impacted on the abundance and community composition. The abundance of the actinomycete PLFA 10Me18:0 was greatest in the grazed and unfertilised treatment, and the PCR–DGGE molecular profiles also indicated that inorganic N fertiliser impacted on the community composition. In a previous study on different soils at the same experimental site, the abundance of PLFA 10Me18:0 was found to be greatest in unfertilised soils and community composition of actinomycetes was effected by both soil drainage and inorganic N fertiliser (Clegg et al., 2003). In addition to the aforementioned factors, previous studies have also reported that abundance of PLFA 10Me18:0 was also sensitive to changes in soil depth (Fritze et al., 2000) and liming (Frostega˚rd et al., 1993), and it appears that abundance of the actinomycete PLFA10Me18:0 is an indicator of change in soil conditions.
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
In summary, the findings of this study provide evidence that both cattle grazing and inorganic N fertiliser additions impact on the microbial composition of soils. Previous studies had reported changes in the production rates of CO2–N2O–NO2 emissions, Nmineralisation and microbial biomass, however, it was unclear from those studies whether differences in transformation rates where due to changes in the activities of micro-organisms or shifts in community composition. The results of this study demonstrated that management regime does impact on the general microbial community composition and now the focus of future studies is to make that specific mechanistic link between soil process and microbial species.
Acknowledgements The Institute of Grassland and Environmental Research is supported by the Biotechnology and Biological Sciences Research Council.
References Antil, R.S., Lovell, R.D., Hatch, D.J., Jarvis, S.C., 2001. Mineralisation of nitrogen in permanent pastures amended with fertilizer or dung. Biol. Fertil. Soil 33, 132–1388. Ba˚a˚th, E., Anderson, T.-H., 2003. Comparison of soil fungal/bacterial ratios in a pH gradient using physiological and PLFA-based techniques. Soil Biol. Biochem. 35, 955–963. ˚ ., 1996. Changes in soil Bardgett, R.D., Hobbs, P.J., Frostega˚rd, A fungal:bacterial biomass ratios following reductions in the intensity of management of an upland grassland. Biol. Fertil. Soils 22, 261–264. Bardgett, R.D., Leemans, D.K., Cook, R., Hobbs, P.J., 1997. Seasonality of the soil biota of grazed and ungrazed hill grasslands. Soil Biol. Biochem. 29, 1285–1294. Bligh, E.G., Dyer, W.J., 1959. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917. Cavigelli, M.A., Robertson, G.P., Klug, M.J., 1995. Fatty acid methyl ester (FAME) profiles as measures of soil microbial community structure. Plant Soil 170, 99–113. Clayton, S.J., Clegg, C.D., Murray, P.J., Gregory, P.J., 2005. Determination of the impact of continuous defoliation of Lolium perenne and Trifolium repens on bacterial and fungal community structure in rhizosphere soil. Biol. Fertil. Soil 41, 109–115. Clegg, C.D., Lovell, R.D.L., Hobbs, P.J., 2003. The impact of grassland management regime on the community structure of selected bacterial groups in soils. FEMS Microbiol. Ecol. 43, 263–270.
81
Clegg, C.D., Ritz, K., Griffiths, B.S., 2000. %G + C profiling and cross hybridisation of microbial DNA reveals great variation in below-ground community structure in UK upland grasslands. Appl. Soil Ecol. 14, 125–134. DEFRA, 2002. The Environment in Your Pocket. Department for Environment and Rural Affairs, London. Federle, T.W., 1986. Microbial distribution in soil: new techniques. In: Megusar, F., Gantar, M. (Eds.), Perspectives in Microbial Ecology. Slovene Society for Microbiology, Ljubljana, Slovenia, pp. 493–498. Frey, S.D., Elliot, E.T., Paustian, K., 1999. Bacterial and fungal abundance and biomass in conventional and no-tillage agroecosystems along two climatic gradients. Soil Biol. Biochem. 31, 573–585. Fritze, H., Pietika¨inen, J., Pennanen, T., 2000. Distribution of microbial biomass and phospholipid fatty acids in podzol profiles under coniferous forest. Eur. J. Soil Sci. 51, 565–573. ˚ ., Ba˚a˚th, E., Tunlid, A., 1993. Shifts in the structure of Frostega˚rd, A soil microbial communities in limed forests as revealed by phospholipid fatty acid analysis. Soil Biol. Biochem. 25, 723–730. Garland, J.L., Mills, A.L., 1991. Classification and characterisation of heterogenous microbial communities on the basis of patterns of community-level sole-carbon source utilisation. Appl. Environ. Microbiol. 57, 2351–2359. Gill, K., Jarvis, S.C., Hatch, D.J., 1995. Mineralization of nitrogen in long-term pasture soils: effects of management. Plant Soil 172, 153–162. Gordon, I.J., Duncan, P., 1993. Objectives for production and conservation in grasslands: effect of large grazing ungulates. In: Haggar, R.J., Peel, S. (Eds.), Grassland Management and Nature Conservation, Occasional Symposium No. 28, British Grassland Society. Gray, N.D., Hastings, R.C., Sheppard, S.K., Loughnane, P., Lloyd, D., McCarthy, A.J., Head, I.M., 2003. Effects of soil improvement treatments on bacterial community structure and soil processes in an upland grassland soil. FEMS Microbiol. Ecol. 46, 11–22. Grayston, S.J., Griffith, G.S., Mawdsley, J.L., Campbell, C.D., Bardgett, R.D., 2001. Accounting for variability in soil microbial communities of temperate upland grassland ecosystems. Soil Biol. Biochem. 33, 533–351. Hatch, D.J., Lovell, R.D., Antil, R.S., Jarvis, S.C., Owen, P.M., 2000. Nitrogen mineralization and microbial activity in permanent pastures amended with nitrogen fertilizer or dung. Biol. Fertil. Soil 30, 288–293. Hatch, D.J., Sprosen, M.S., Jarvis, S.C., Ledgard, S.F., 2002. Use of labelled nitrogen to measure gross and net rates of mineralization and microbial activity in permanent pastures following fertilizer applications at different time intervals. Rapid Commun. Mass Spectrom. 16, 2172–2178. Heuer, H., Kresk, M., Baker, P., Smalla, K., Wellington, E.M.H., 1997. Analysis of actinomycete communities by specific amplification of genes encoding 16S rRNA and gel-electrophoretic separation in denaturing gradients. Appl. Environ. Microbiol. 63, 3233–3241. Holland, J.N., 1995. Effects of above ground herbivory on soil microbial biomass in conventional and no-tillage agroecosystems. Appl. Soil Ecol. 2, 275–279.
82
C.D. Clegg / Applied Soil Ecology 31 (2006) 73–82
Hopkins, A., Hopkins, J.J., 1993. UK grasslands now: agricultural production and nature conservation. In: Haggar, R.J., Peel, S. (Eds.), Grassland Management and Nature Conservation, Occasional Symposium No. 28, British Grassland Society. Kennedy, N., Brodie, E., Connolly, J., Clipson, N., 2004. Impact of lime, nitrogen and plant species on bacterial community structure in grassland microcosms. Environ. Microbiol. 6, 1070– 1080. Klein, D.A., Paschke, M.W., 2000. A soil microbial community structural-functional index: the microscopy-based total/active/ active fungal/bacterial (TA/AFB) biovolumes ratio. Appl. Soil Ecol. 14, 257–268. Lichtenstein, C., Draper, J., 1985. Genetic engineering of plants. In: Glover, D.M. (Ed.), DNA Cloning, vol. 2. IRL Press, Oxford, pp. 67–120. Lovell, R.D., Hatch, D.J., 1998. Stimulation of microbial activity following spring applications of nitrogen. Biol. Fertil. Soils 26, 28–30. Lovell, R.D., Jarvis, S.C., 1996a. Effects of urine on soil microbial biomass, methanogenesis, nitrification and denitrification in grassland soils. Plant Soil 186, 265–273. Lovell, R.D., Jarvis, S.C., 1996b. Effect of cattle dung on soil microbial biomass C and N in a permanent pasture soil. Soil Biol. Biochem. 28, 291–299. Lovell, R.D., Jarvis, S.C., Bardgett, R.D., 1995. Soil microbial biomass and activity in long-term grassland: effects of management changes. Soil Biol. Biochem. 27, 969–975. MacDuff, J.H., Jackson, S.B., 1992. Influx and efflux of nitrate and ammonium in Italian ryegrass and white clover roots: comparisons between effects of darkness and defoliation. J. Exp. Bot. 43, 525–535. Mawdsley, J.L., Bardgett, R.D., 1997. Continuous defoliation of perennial ryegrass (Lolium perenne) and white clover (Trifolium repens) and associated changes in the composition and activity of the microbial population of an upland grassland soil. Biol. Fertil. Soil 24, 52–58. Mikola, J., Yeates, G.W., Wardle, D.A., Barker, G.M., Boner, K.I., 2001. Response of soil food-web structure to defoliation of different plant species combinations in an experimental grassland community. Soil Biol. Biochem. 33, 205–214. Muyzer, G., De Waal, E.C., Uitterlinden, A.G., 1993. Profiling of complex microbial populations by denaturing gradient gel elec-
trophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59, 695–700. Parkin, T.B., Starr, J.L., Meisinger, J.J., 1987. Influence of sample size on measurement of soil denitrification. Soil Sci. Soc. Am. J. 51, 1492–1501. Paterson, P., Sim, A., 1999. Rhizodeposition and C-partitioning of Lolium perenne in axenic culture affected by nitrogen supply and defoliation. Plant Soil 216, 155–164. Ritz, K., McNicol, J.W., Nunan, N., Grayston, S., Millard, P., Atkinson, D., Gollotte, A., Habeshaw, D., Boag, B., Clegg, C.D., Griffiths, B.S., Wheatley, R.E., Glover, L.A., McCaig, A.E., Prosser, J.I., 2004. Spatial structure in soil chemical and microbiological properties in an upland grassland. FEMS Microbiol. Ecol. 49, 191–205. Tallowin, J.R.B., 1996. Effects of inorganic fertilisers on flower-rich hay meadows: a review using a case study on the Somerset Levels, UK. Grassland Forage Abstr. 66, 147–152. van Elsas, J.D., Duarte, G.F., Keijzer-Wolters, A., Smit, E., 2000. Analysis of the dynamics of fungal communities in soil via fungal specific PCR of soil DNA followed by denaturing gradient gel electrophoresis. J. Microbiol. Methods 43, 133–151. Vinten, A.J.A., Lewis, D.R., Fenlon, D.R., Leach, K.A., Howard, R., Svoboda, I., Ogden, I., 2002. Fate of Escherichia coli and Escherichia coli 0157 in soils and drainage water following cattle slurry application at 3 sites in southern Scotland. Soil Use Manage. 18, 223–231. Vinten, A.J.A., Douglas, J.T., Lewis, D.R., Aitken, M.N., Fenlon, D.R., 2004. Relative risk of surface water pollution by E. coli derived from faeces of grazing animals compared to slurry application. Soil Use Manage. 20, 13–22. White, S.L., Sheffield, R.E., Washburn, S.P., King, L.D., Green, J.T., 2001. Spatial and time distribution of dairy cattle excreta in an intensive pasture system. J. Environ. Qual. 30, 2180–2187. 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. Yeates, G.W., Bardgett, R.D., Cook, R., Hobbs, P.J., Bowling, P.J., Potter, J.F., 1997. Faunal and microbial diversity in three welsh grassland soils under conventional and organic management regimes. J. Appl. Ecol. 34, 453–470.