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No-till soil management increases microbial biomass and alters community profiles in soil aggregates
Applied Soil Ecology 46 (2010) 390–397
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No-till soil management increases microbial biomass and alters community profiles in soil aggregates B.L. Helgason a,∗ , F.L. Walley b , J.J. Germida b a b
Agriculture and Agri-Food Canada, Saskatoon Research Centre, 107 Science Place, Saskatoon, SK, S7N 0X2, Canada Department of Soil Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada
a r t i c l e
i n f o
Article history: Received 19 February 2010 Received in revised form 30 September 2010 Accepted 5 October 2010 Keywords: No-till Tillage Aggregates Microbial biomass Microbial community
a b s t r a c t Aggregation is important for soil functioning, providing physical protection of organic matter and microbial inhabitants. Tillage disrupts aggregates, increases wind and water erosion of soils and exposes formerly protected organic matter to decomposition and losses. Microbial biomass and community dynamics in dry-sieved aggregate-size classes from long-term no-till (NT) and conventionally tilled (CT) soils were examined using phospholipid fatty acid analysis (PLFA). Bacterial, fungal, and total biomass were up to 32% greater in NT compared to CT aggregates. Aggregate size also affected microbial biomass, which was highest in the 1–2 mm size class. Arbuscular mycorrhizal fungi (AMF) were particularly affected by tillage disturbance with increases of 40–60% among aggregate-size classes in NT vs. CT, but glomalin related soil protein concentration was not different between tillage treatments or among aggregate-size classes. Bacterial stress biomarkers were higher in CT than NT aggregates but were not significantly correlated with total C, total N or C:N ratio, indicating that the physiological status of bacteria within aggregates was not simply governed by the quantity of available resources. Ordination analysis of PLFA profiles demonstrated a shift in microbial community structure between NT and CT aggregates, correlated with AMF abundance in NT aggregates and increased bacterial stress biomarkers in CT aggregates. Our results demonstrated greater microbial biomass and altered microbial community structure in NT vs. CT aggregates. This work demonstrates that tillage management influences microbial community structure within aggregates and may provide a potential explanation for differences in process rates observed in NT vs. CT soils. Further research into the processes that govern community structure in aggregates from NT and tilled soils is needed to better understand how the interaction of microorganisms with their physical environment affects nutrient turnover and availability. Crown Copyright © 2010 Published by Elsevier B.V. All rights reserved.
1. Introduction Aggregation is an important facet of soil structure, providing resistance to wind and water erosion, physical protection of organic matter and microsites for microbial activity. Agroecosystem productivity and sustainability are dependent on the maintenance of key microbial processes. Aggregates provide habitat for microbial activity and understanding how management affects the distribution of microbial functional groups among aggregates will lead to a better understanding of the regulation of microbial processes including soil C storage, nutrient turnover and trace gas emissions. The primary mechanisms to influence soil microbial communities are through the alteration of soil structure or substrate inputs (i.e., crop residues) (Elliott and Coleman, 1988). In this way, soil biological activity and the physical soil environment are related
∗ Corresponding author. Tel.: +1 306 975 6510; fax: +1 306 966 4226. E-mail address: [email protected] (B.L. Helgason).
through dynamic feedback mechanisms which inextricably link these two primary foundations of soil functioning (Young and Ritz, 2000). Tillage affects soil aggregation directly through physical disruption, and indirectly through influences on the broader biological and chemical soil environment (Young and Ritz, 2000). Macroaggregate stability is especially susceptible to agronomic practices (Six et al., 2004). Macroaggregates are stabilized by plant roots and fungal hyphae, as well as by the byproducts of microbial metabolism (Tisdall and Oades, 1982) and they provide habitat for soil bacteria while spatially protecting organic matter. Tillage affects both the level of aggregation and the rate of aggregate turnover (Six et al., 1998). Disruption during tillage events releases particulate organic matter from macroaggregates and increases organic matter turnover (Six et al., 2000). As a result, slower macroaggregate turnover under NT has been suggested as a potential mechanism for increased C storage in NT soils (Six et al., 1999). The formation of microaggregates within macroag-
0929-1393/$ – see front matter. Crown Copyright © 2010 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2010.10.002
B.L. Helgason et al. / Applied Soil Ecology 46 (2010) 390–397
gregates serves to protect stabile C whereas macroaggregates are more important for the storage of labile C (Six et al., 2000; Bossuyt et al., 2002; Mikha and Rice, 2004). Beare et al. (1992) concluded that fungi contribute more to the formation of aggregates in NT than CT soils and Six et al. (2000) proposed that stable microaggregate formation within macroaggregates is vital for C sequestration in NT soils. Microbial biomass, including that of saprotrophic fungi and AMF often increases under NT management (Helgason et al., 2009; Muruganandam et al., 2009; White and Rice, 2009). However, relatively little is known about the mechanisms that drive aggregate turnover and protect different forms of C within aggregates (Six et al., 2004; Abiven et al., 2009). Separation of aggregates into multiple size classes can by done in many ways (e.g., dry sieving fresh or air-dry soil as well as wet sieving of fresh or air-dry soil). The means by which the aggregates are obtained affects the way in which aggregates are both defined and potentially linked to function in the broader soil context (Ashman et al., 2009). It is common to assess water-stable aggregates (WSA) in the study of soil C dynamics (Six et al., 1999; Wright and Hons, 2005; Yamashita et al., 2006; Olchin et al., 2008; White and Rice, 2009) and the bulk of recent aggregate research has employed wet sieving of air-dried aggregates. However, it is clearly demonstrated that the method of aggregate separation affects the resulting distribution of aggregate sizes as well as their chemical (Sainju, 2006) and biological (Ashman et al., 2009; Paradelo and Barral, 2009) characteristics. Sainju (2006) compared aggregate separation methods and concluded that dry sieving moist soil can be used as a reliable method of separating aggregates. Dry sieving methods have previously been used in studies of microbiological properties of aggregates (Schutter and Dick, 2002; Muruganandam et al., 2009, 2010). Other studies of microbial communities directly associated with aggregates are few and most information regarding aggregate microbial communities is indirectly linked to the aggregates themselves by evaluation of bulk soil communities (e.g., Väisänen et al., 2005). Peixoto et al. (2006) examined 16S rRNA genes in NT vs. CT bulk soils and found that the NT community was more similar to that of an adjacent soil under forested vegetation than to the tilled soil which they attributed to changes in soil structure, including increased mean weight diameter of aggregates under NT. Muruganandam et al. (2010) recently found that microbial community composition differed between aggregates from NT and tilled soils, but were not different among aggregate-size classes. Schutter and Dick (2002) showed differences in aggregate FAME profiles as a function of sampling date and winter cover cropping, but to a lesser extent by aggregate size. Previous work in the same long-term NT and CT soils at Swift Current, SK, Canada, demonstrated an increase in total, bacterial and fungal biomass (Helgason et al., 2009), but not community structure (Helgason et al., 2010) in bulk soils. Given the enormous influence that soil heterogeneity can exert on microbially-mediated processes (Young and Ritz, 2000), aggregate microenvironments have the potential to greatly affect overall soil functioning. In this way, differences in soil functioning between CT and NT soils may be partially explained by differences in aggregate microhabitats. We hypothesized that because macroaggregates are particularly susceptible to physical disruption by tillage, shifts in microbial community structure may occur among naturally formed field aggregates in NT and CT soils. To test this hypothesis, we examined microbial communities in aggregates from a long-term experiment where physical disturbance from tillage intensity varied, but cropping system management was otherwise held constant. Phospholipid fatty acid analysis was used to evaluate the abundance and community structure of soil microorganisms in dry-sieved aggregate-size fractions from NT and CT soils.
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2. Materials and methods 2.1. Soil collection and aggregate isolation Aggregates were obtained from a long-term tillage experiment in a semi-arid prairie region at Swift Current, SK, Canada. The experiment is a randomized complete block design (n = 4) with individual plot sizes of 15.24 m × 32.00 m. The experiment was initiated in 1981 and is continuously cropped in a four-year rotation of wheat–lentil–wheat–pea. Tillage disturbance in the CT soils was relatively low, involving one pre-seeding pass with a heavy-duty cultivator and mounted harrows. Both CT and NT plots were seeded using an air-drill equipped with knife openers. Soils were sampled on April 27, 2006 (which followed a lentil crop in 2005), prior to seeding and any pre-seeding tillage disturbance in the CT plots. This sampling date was chosen to minimize the effect of in-season influences, including plant growth and fertilization. Samples (n = 10 per plot) were obtained using a hand trowel from the 0- to 10-cm depth and composited. Soil was stored on ice during transport back to the laboratory for processing. We chose to separate aggregates into five size classes through dry-sieving of fresh soil because both wet sieving and air drying compromised the in situ link between the aggregates obtained and their indigenous microbial inhabitants. Soil was initially passed through a 4-mm sieve. Naturally formed field aggregates (Pikul et al., 2009) were isolated manually by dry sieving 300 g of fresh soil (moisture content ca. 10%) on a series of 4 sieves (2 mm; 1 mm; 500 m, 250 m). Sieves were gently rotated 90 times at a rate of 30 rotations per minute in the following order: 30 rotations clockwise, 30 rotations counterclockwise followed by 15 rotations clockwise and 15 rotations counterclockwise. Aggregate distribution was determined by weight from each size class. This gentle sieving procedure aimed to minimize excessive disturbance of larger aggregates and was tested to ensure consistent and repeatable aggregate distribution in both NT and CT soils. No attempt was made to separate microaggregates from within macroaggregates and the aggregate-size classes chosen here primarily correspond to commonly defined macroaggregate fractions (i.e., >250 m) with only the smallest size fraction representing microaggregates. 2.2. General soil characteristics Gravimetric moisture content was determined by measuring moisture loss from fresh soil by mass after drying at 105 ◦ C for 48 h. Aggregate sand content (50–500 m particles) was determined following dispersal and sonication (Pinno and Belanger, 2008) by laser scattering particle-size analysis (using a Partic LA-950 (Horiba, Inc., Kyoto, Japan). Total C (TC) and total N (TN) were measured by dry combustion using a LECO CNS-2000 analyzer (LECO Instruments, Ltd., St. Joseph, MI). 2.3. Phospholipid fatty acid analysis PLFA was performed using the modified method of White et al. (1979), based on the original method of Bligh and Dyer (1959). Briefly, fatty acids were extracted from 4.0 g of lyophilized, ground soil using a single phase chloroform, methanol, phosphate buffer solution. Fatty acids were separated on a solid phase extraction column (0.50 g Si; Varian Inc., Mississauga, ON), phospholipids were methylated and resulting fatty acid methyl esters were analyzed using a Hewlett Packard 5890 Series II gas chromatograph with a 25 m Ultra 2 column (J&W Scientific). Peaks were identified using fatty acid standards and MIDI identification software (MIDI Inc., Newark, DE) and quantified based on the addition of internal standard methyl nonadecanoate (19:0). Total biomass was calculated as the sum of all identified PLFA peaks (Zelles et al., 1992). Rela-
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tive fungal and bacterial biomass in NT and CT soils was assessed using the fungal biomarker 18:26,9 and the sum of 13 bacterial biomarkers (i14:0, i15:0, a15:0, i16:0, 16:17c, 10Me16:0, i17:0, a17:0, cy17:0, 10Me17:0, 18:17, 10Me18:0, cy19:0) (Bååth and Anderson, 2003). Biomarkers used to represent gram positive bacteria (Gr+) were i14:0, i15:0, a15:0, i16:0, i17:0, a17:0 (Hedrick et al., 2005). Biomarkers used for gram negative bacteria (Gr−) were 16:17t, 16:19c, 16:17c, 18:17c, 18:19c, cy17:0, and cy19:0 (Macdonald et al., 2004). Biomass of AMF was evaluated using the PLFA biomarker 16:15c (Olsson, 1999). Physiological stress biomarkers denoted as Stress 1 and Stress 2 represent the ratios of cy17:0 to 16:17c and cy19:0 to 18:17c, respectively (Grogan and Cronan, 1997). 2.4. Glomalin extraction and quantification Easily extractable glomalin-related soil protein (GRSP) was obtained by extracting 1.0 g of soil in 8 mL of 20 mM sodium citrate buffer (pH 7.0) and autoclaving for 30 min at 121 ◦ C. Following extraction, soil was pelleted by centrifugation at 5000 × g for 15 min and the volume of supernatant measured. Glomalin related soil protein was measured (n = 2) using the Bradford total protein assay using bovine serum albumen as a standard (Bradford, 1976; Wright et al., 1996). 2.5. Statistical analysis Analysis of variance and correlation analyses were performed using SPSS version 13.0 for Windows (SPSS Inc., 2004). Prior to analysis, PLFA data were transformed using the log(mol% + 1) transformation but are presented here as untransformed data. Homogeneity of variance was assessed using Levine’s test. Relationships between soil characteristics, GRSP and PLFA biomarkers were assessed using Pearson’s correlation coefficient. Non-metric multidimensional scaling (MDS) using the Sørensen distance measure was carried out in the Autopilot Slow and Thorough analysis option in PCOrd V.5.0 (McCune and Grace, 2002). A random starting point was used for initial analysis in which stress was minimized. A starting configuration for the final ordination was then supplied from the least-stress solution obtained initially. Significance testing was performed using Monte Carlo analysis. A multi-response permutation procedure (MRPP) was performed using the Sørensen distance measure to test for differences between a priori groups and was carried out in PCOrd V.5.0.
3. Results and discussion Aggregates were separated using dry sieving and the proportional distribution by mass of different sized aggregates for NT and CT soils is listed in Table 1. Sand content of the aggregates ranged from 35 to 47% and was significantly (P < 0.07) greater in NT than CT as well as different among aggregate sizes (P < 0.001) (Table 1). Total C and TN, PLFA and GRSP data were adjusted for sand content to account for differences that result from physical sorting of nonaggregate associated sand particles (Elliott et al., 1991) and have been presented on a sand-free soil dry weight basis. Tillage interacted with aggregate size (P < 0.08) to affect the mass distribution of aggregates. There were more macroaggregates in NT than CT, except in the 1–2 mm size class (Table 1). This is in agreement with other studies that examined water-stable macroaggregates in NT vs. CT soils (Wright and Hons, 2005; Zibilske and Bradford, 2007; Alvarez and Steinbach, 2009) but is in contrast to a recent study of dry-sieved aggregates by Muruganandam et al. (2009) who found no effect of tillage on aggregate distribution. No-till aggregates had significantly higher TC (P < 0.06) and TN (P < 0.04) than CT aggregates, but C:N ratio did not differ significantly as a function of tillage (Table 1). Earlier work demonstrated that there was no significant difference in TC or TN content between NT and CT in bulk soils (not expressed on a sand-free basis) (Helgason et al., 2009). However, C to N ratio was lower in NT bulk soils, as was the non-significant trend with NT aggregates (Table 1) which may indicate differences in substrate chemistry within NT and CT aggregates. There was no significant difference in TC, TN or C:N ratio among aggregate-size classes. Total, bacterial and fungal biomass were greater in NT than CT aggregates and varied significantly among different aggregate-size classes (Fig. 1; Table 2). While biomass differed among tillage treatments, the relative abundance of bacteria and fungi (i.e., proportion of the total community, expressed as mol% of total PLFA) were not different between NT and CT aggregates. Increased microbial biomass is commonly found in NT vs. CT soils (Frey et al., 1999; Drijber et al., 2000; Bailey et al., 2002; Feng et al., 2003; Spedding et al., 2004; Minoshima et al., 2007; White and Rice, 2009) and was previously measured in the bulk soil (0–5 cm) at this experimental site (Helgason et al., 2009). Muruganandam et al. (2010) found greater relative abundance of fungi in NT aggregates which was positively correlated with the activity of various enzymes associated with N mineralization, linking increased fungal abundance to soil functioning. A second study (Muruganandam et al., 2010) demonstrated that increased microbial biomass, rather than altered community composition resulted in greater N transformation rates.
Table 1 Treatment means (n = 4) and analysis of variance (ANOVA) for moisture content, aggregate size distribution and sand content of different no-till (NT) and conventional-till (CT) aggregates expressed as a percent of the total sample (dry weight basis). Tillage
Aggregate size
Soil moisture (g kg−1 )
Aggregate distribution (%)
Sand content (%)
Total Ca (g kg−1 )
Total Na (g kg−1 )
C:N
NT CT NT CT NT CT NT CT NT CT
2–4 mm
113 98 109 98 111 101 104 99 86 8.3
36.0 30.6 15.4 17.5 20.3 19.7 16.8 15.5 11.6 16.7
38.3 33.5 41.5 39.5 36.5 35.0 40.5 36.5 46.5 37.8
29.6 27.1 33.4 30.7 29.5 27.7 30.4 27.6 30.3 28.2
3.56 3.07 3.79 3.47 3.41 3.12 3.66 3.17 3.63 2.87
8.43 8.95 9.00 9.08 8.79 9.08 8.46 8.87 8.57 9.85
ANOVA
Tillage (T) Aggregate size (A) TxA
P < 0.017 P < 0.003 P < 0.813
P < 0.908 P < 0.000 P < 0.078
P < 0.070 P < 0.002 P < 0.948
P < 0.065 P < 0.297 P < 0.997
P < 0.040 P < 0.798 P < 0.966
P < 0.252 P < 0.925 P < 0.938
a
1–2 mm 500 m to 1 mm 250–500 m <250 m
Data presented on a sand-free basis.
B.L. Helgason et al. / Applied Soil Ecology 46 (2010) 390–397
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Table 2 Analysis of variance (ANOVA) probability values for bacterial, fungal, total and fungal:bacterial ratio (F:B) of PLFA biomarkers in dry-sieved aggregates from long-term no-till (NT) and conventional-till (CT) soils at Swift Current, Saskatchewan, Canada. a
Tillage (T) Aggregate size (A) TxA a
a
Bacterial PLFA
a
Fungal PLFA
Total PLFA
nmol g−1 soil
mol%
nmol g−1 soil
mol%
nmol g−1 soil
0.000 0.025 0.447
0.318 0.001 0.910
0.001 0.000 0.093
0.722 0.000 0.813
0.000 0.036 0.442
F:B
0.628 0.000 0.789
Data presented on a sand-free basis.
Indirect evidence suggests microbial functional groups differentially inhabit and control aggregate-size fractions. Larger aggregates had a higher ratio of fungal:bacterial (F:B) biomass and a greater (P < 0.001) relative abundance of fungi, which is in agreement with aggregate formation theory (Six et al., 2004). Simpson et al. (2004) measured greater amino sugar C in WSA of NT over CT soils, indicating that more microbial-derived C is stored in aggregates in NT soils. Guggenberger et al. (1999) found that glucosamine, a fungal-derived amino sugar, accumulated in aggregates of NT soils which coincided with higher fungal biomass in the bulk soil. The current study relates fungal and bacterial biomass directly with aggregates of different sizes and shows that the F:B biomass ratio decreases with decreasing aggregate size. Fungi and roots are involved in macroaggregate formation, physically binding soil particles (Tisdall and Oades, 1982; Oades, 1984; Gupta and Germida, 1988; Chantigny et al., 1997; Bossuyt et al., 2001). Decreasing relative abundance of fungi vs. bacteria with decreasing aggregate size is consistent with this mechanism of aggregate formation. It is interesting to note that similar to the bulk soil (Helgason et al., 2009), while both fungal and bacterial biomass were greater in NT aggregates, there was no significant difference in the ratio of fungi vs. bacteria. Based on the research of Simpson et al. (2004) and Guggenberger et al. (1999), it seems fungi confer
greater influence on aggregate stability in NT than CT soils due to the greater overall abundance of fungal cell wall residues as a result of their recalcitrance, rather than a proportional increase in fungal biomass, at the expense of bacteria. Similar to total bacterial biomass, biomass of Gr+ and Gr- was higher in NT than CT aggregates and was greatest in the 1–2-mm aggregate-size fraction (Table 3). The relative abundance (mol %) of Gr+ and Gr− bacterial PLFA was not affected by either tillage or aggregate size (Table 3). These results are similar to the findings of Muruganandam et al. (2009) who found no effect of tillage on relative abundance of Gr+ or Gr− biomarkers in aggregates. Physiological stress biomarkers were significantly higher (P < 0.05) in CT aggregates but were not different among aggregatesize classes (Table 3). These stress biomarkers were correlated with microbial PLFA profiles in CT aggregates and with the functional group biomarkers in both NT and CT aggregates but not with TC, TN, or C:N ratio which were greater in NT than CT aggregates, indicating that it was not simply the overall quantities of C and N that affected community structure. Organic matter distribution is known to differ between aggregate size fractions from NT and CT soils (Six et al., 1999). Further investigation of the link between community structure and the chemistry of C and N resources within aggregates is needed. A recent study by Plante et al. (2009) found increased respi-
Fig. 1. Bacterial and fungal PLFA biomarkers (sand-free basis), total PLFA extracted and fungal:bacterial (F:B) PLFA ratio in aggregates from long-term no-till (NT) and conventional-till (CT) soils. Error bars represent standard deviations (n = 4).
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Table 3 Treatment means and analysis of variance (ANOVA) for absolute and relative quantity of gram positive (Gr+), gram negative (Gr−) bacterial and stress PLFA biomarkers and glomalin related soil protein in aggregates from long-term NT and CT soils. Tillage
Aggregate size
Gr+ (nmol g−1 soil)
Gr− (nmol g−1 soil)
Gr+ (mol%)
Gr− (mol%)
Stress 1
Stress 2
a
NT CT NT CT NT CT NT CT NT CT
2–4 mm
14.0 11.9 17.7 12.1 14.8 11.2 14.7 10.7 14.0 10.7
15.5 14.2 21.3 14.7 17.1 13.2 16.9 13.5 15.8 12.6
21.8 20.7 20.7 20.7 21.2 20.9 21.6 20.4 21.4 20.8
21.4 24.6 24.8 25.2 24.3 24.7 24.9 25.6 24.4 25.1
0.265 0.347 0.246 0.352 0.260 0.364 0.260 0.362 0.240 0.337
0.206 0.259 0.211 0.288 0.198 0.219 0.169 0.226 0.175 0.205
1.13 1.00 1.16 1.12 1.12 1.06 0.99 1.05 1.01 1.08
ANOVA
Tillage (T) Aggregate size (A) TxA
P < 0.000 P < 0.043 P < 0.361
P < 0.000 P < 0.015 P < 0.222
P < 0.159 P < 0.754 P < 0.735
P < 0.088 P < 0.397 P < 0.998
P < 0.000 P < 0.866 P < 0.990
P < 0.006 P < 0.137 P < 0.817
P < 0.187 P < 0.130 P < 0.740
a
1–2 mm 500 m to 1 mm 250–500 m <250 m
GRSP (mg g−1 )
Data presented on a sand-free basis.
ration rates from aggregates incubated under elevated temperature were attributable to increased microbial biomass. Differences in specific respiration rates in their study suggested microbial community composition rather than simple biomass measures needs to be assessed to understand the processes governing microbial substrate utilization within aggregates. Saprotrophic fungi and AMF produce abundant hyphae in soil and contribute to the formation of macroaggregates (Tisdall and Oades, 1982). Biomass of AMF was significantly greater (P < 0.001) in NT vs. CT (Fig. 2). In four out of five size classes, the AMF biomarker was 40–60% higher and in the 1–2 mm size class the AMF biomarker was 2-fold greater in NT than CT, indicating a strong effect of tillage disturbance. Relative abundance of AMF was also significantly higher (P < 0.001) in NT than CT aggregates (not shown). Fungal biomass decreased with aggregate size (Fig. 1), whereas AMF biomass remained constant among the three smallest size classes (Fig. 2) resulting in a ratio of AMF:fungi that was inversely related to aggregate size (Fig. 3). This suggests that AMF may be exploiting a spatial niche within small aggregates that saprotrophic fungi are either less able or less apt to explore. Both saprotrophic and AMF hyphae are sensitive to physical disruption by tillage (Elliott and Coleman, 1988; Wardle, 1995). Decreased AMF hyphal length and inoculum potential as a result of physical soil disturbance has been clearly demonstrated (McGonigle and Millar, 1996; Kabir et al., 1999). Wortmann et al. (2008) found a slower recovery of AMF than other microbial groups following a one time tillage event in long-term NT soils, indicating that AMF may be particularly susceptible to tillage stress.
An indirect, but potentially important role of AMF contribution to macroaggregate formation occurs through promotion of root growth (Bearden and Petersen, 2000). Roots bind soil particles, release exudates and provide particulate organic matter that facilitates aggregate formation and stability (Tisdall and Oades, 1982; Gale et al., 2000; Márquez et al., 2004; Six et al., 2004). This dominance of AMF in NT aggregates agrees with Wilson et al. (2009) who found that AMF biomass was a remarkably good predictor of soil aggregation in grassland soils. Glomalin, an abundant proteinaceous material in soil, coats the surfaces of hyphae and soil particles (Wright et al., 2007) and is thought to confer water-stability to aggregates by acting as a binding agent. While the origin of glomalin remains unproven (Rillig, 2004; Rosier et al., 2006), it is circumstantially linked to AMF and has a relatively long turnover time, far longer than hyphae. In our study, easily extractable GRSP did not differ among tillage treatments or aggregate fractions (Table 3). Correlation between GRSP and AMF biomass was good in CT aggregates (r = 0.76), but there was no relationship in NT aggregates (r = 0.04). In grassland soils subjected to various stresses, Wilson et al. (2009) found a continuous linear relationship between AMF biomass and aggregation (WSA). Importantly, they did not detect a threshold above which AMF abundance ceased to affect aggregation. It is possible that the lack of positive correlation seen here in the NT aggregates could have been caused by a change in growth pattern of the AMF. Biomass of AMF was measured using the PLFA biomarker 16:15c which is present in hyphae and spores. Because glomalin is deposited in
NT NT IT CT
7
4.0
-1
AMF PLFA biomarker -1 (nmol g soil)
8
AMF PLFA (nmol g soil)
5.0
9
6 5 4 3 2 1
3.0
2.0
1.0
NT 2-4mm NT 250um-0.5mm CT 1-2mm CT <250um
0 2-4mm
1-2mm
500µm1mm
250µm500µm
<250µm
Aggregate size class Fig. 2. Arbuscular mycorrhizal fungi (AMF) PLFA biomarker (sand-free basis) in aggregates from long-term no-till (NT) and conventional-till (CT) soils. Error bars represent standard deviations (n = 4).
0.0 0.0
1.0
NT 1-2mm NT <250um CT 500um-1mm
2.0
NT 500um-1mm CT 2-4mm CT 250-500um
3.0
4.0
5.0
-1
Fungal PLFA(nmol g soil) Fig. 3. Relationship between fungal (18:2w6,9) and arbuscular mycorrhizal fungi (AMF) (16:15c) biomarkers in aggregates from long-term no-till (NT) and conventional-till (CT) soils.
B.L. Helgason et al. / Applied Soil Ecology 46 (2010) 390–397
Axis 2 (35%)
AMF hyphal walls, a significant increase in sporulation without an increase in hyphal growth could decouple the relationship between AMF biomarker and GRSP. Wright et al. (1999) showed a strong linear relationship between GRSP and aggregate stability in soils transitioning from CT to NT and that GRSP was highly correlated with water-stable aggregation (measured in the 1–2 mm size class) across a wide range of soils (Wright and Upadhyaya, 1998). A more recent paper (Wright et al., 2007) reported that GRSP increased as water-stable aggregate size increased in NT soils, but remained constant across aggregatesize classes in disturbed soils (including a CT treatment). In the present study of dry-sieved aggregates, GRSP did not change significantly among aggregate-size classes in either tillage treatment. The lack of relationship between dry-sieved aggregate-size distribution and GRSP seen here supports the theory proposed by Wright et al. (2007) that glomalin acts as a microbial glue and of Wilson et al. (2009) that AMF are instrumental in binding microaggregates together into macroaggregates. Analysis of PLFA profiles using MDS ordination resulted in a 3dimensional solution with a final stress of 12.0 (instability = 0.000) and accounted for 90% of the variability in the data set. Tillage man-
STRESS 1 CT
NT AMF
4. Conclusions
MRPP Tillage Axis 3 (37%)
agement separated communities along Axis 2 and to some extent along Axis 1 (Fig. 4). Microbial stress biomarkers were positively correlated with CT aggregate profiles, while the AMF biomarker was correlated with NT aggregates indicating that physiological stress (e.g., moisture or nutrient limitation) was influential in determining overall community structure in CT aggregates and AMF were influential in NT aggregate communities. It is interesting that ordination analysis of the entire lipid profile separated NT and CT soils, but that the relative abundance (mol%) of microbial biomarkers for different functional groups was not different between tillage treatments. This indicates that the tillage-induced differentiation within the community occurs at a level of organization more complex than broad groupings indicated by PLFA biomarkers. Blackwood et al. (2006) found little difference in bacterial T-RFLP profiles or cell counts between aggregate interiors and exteriors. However, they found greater bacterial biovolume in aggregate interiors. Thus, activity but not cell number, was correlated with C content of the aggregates suggesting that bacterial activity may be related to C concentration. In the present study, community PLFA profiles also differed among aggregate-size classes, in contrast with the findings of Schutter and Dick (2002) who found a minimal influence of aggregate size on community FAME profiles. They speculated that this lack of difference in aggregate community structure was due to the redistribution of organisms among aggregates during tillage. In our study, physical soil disturbance is minimal even in the CT treatment, negating this potential smoothing effect on community structure among aggregate sizes.
STRESS 2
Axis 1 (18%)
A = 0.063 STRESS 2
STRESS 1 CT
P < 0.001 Aggregate size
AMF
A = 0.040
NT
P < 0.007 Final stress 12.0
Axis 2 (35%)
Axis 3 (37%)
395
STRESS 1
STRESS 2 CT AMF NT
Axis 1 (18%)
NT 2-4mm
NT 1-2mm
NT 0.5-1mm
NT 250-500um
CT 2-4mm
CT 1-2mm
CT 0.5-1mm
CT 250-500um
NT <250um CT <250um Fig. 4. Two-dimensional depiction of the three-dimensional non-metric multidimensional scaling (MDS) ordination analysis and multiple response permutation procedure (MRPP) of PLFA profiles from aggregates (final stress = 12.0) in no-till (NT) and conventional-till (CT) soils.
Tillage treatments affected microbial biomass and community structure in aggregates of semi-arid prairie soils. Total microbial biomass, as well as biomass of functional groups, was greater in NT vs. CT aggregates but the relative abundance of different functional groups was not affected by tillage (except for AMF). Ordination analysis of PLFA profiles showed that community structure shifted as a function of tillage, demonstrating a response to changing conditions in aggregates in NT soils at a finer scale than could be detected by functional group biomarkers. Elimination of tillage disturbance promoted AMF, with significant increases in total and relative abundance of AMF in NT aggregates. Given recent evidence of the importance of AMF for soil aggregation (e.g., Wilson et al., 2009) and the stabilization and sequestration of C, promotion of AMF by reducing tillage disturbance is beneficial for sustainable management of agroecosystems. Tillage-induced changes in aggregate microbial community structure observed here were not detected in bulk soils from the same site (Helgason et al., 2010), highlighting the value of studying microbial communities at additional spatial scales. Tillage-induced differences within aggregates may lead to changes in microbial functioning as a possible explanation for differences in crop growth in NT vs. CT soils. While this variation in community structure was demonstrated prior to seeding, a temporal comparison of microbial community dynamics during the growing season would help to determine whether these differences diverge or converge as crop development proceeds and may further explain crop growth and yield characteristics. Further research is needed on the relationship of tillage with microbial community structure and function across aggregate-size fractions. Microscale physical and biological changes in NT and CT soils are not well understood. In order to elucidate how tillage influences soil processes, a more detailed understanding of finescale interactions is needed. Differences in C storage potential exist in NT and CT aggregates, but relatively little is understood about the mechanisms that facilitate C preservation. Relating the chem-
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ical composition of C and N resources within aggregates directly to microbial biomass and community structure is necessary to enhance our understanding of the mechanisms of C storage and nutrient turnover in NT soils. Acknowledgements The authors wish to thank Dr. B. McConkey at the AAFC Swift Current Research Station and Dr. S. Brant at the AAFC Scott Research Station as well as the University of Alberta and Alberta Agriculture and Food for providing access to the long-term tillage trials studied. Technical assistance from Morgan Sather and Corrie Kosty is gratefully acknowledged. This research was supported by Agriculture and Agri-Food Canada and Natural Sciences and Engineering Research Council of Canada (NSERC). References Abiven, S., Menasseri, S., Chenu, C., 2009. The effects of organic inputs over time on soil aggregate stability—a literature analysis. Soil Biol. Biochem. 41, 1–12. Alvarez, R., Steinbach, H.S., 2009. A review of the effects of tillage systems on some soil physical properties, water content, nitrate availability and crops yield in the Argentine Pampas. Soil Tillage Res. 104, 1–15. Ashman, M.R., Hallett, P.D., Brookes, P.C., Allen, J., 2009. Evaluating soil stabilization by biological processes using step-wise aggregate fractionation. Soil Tillage Res. 102, 209–215. Bååth, 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. Bailey, V.L., Smith, J.L., Bolton Jr., H., 2002. Fungal-to-bacterial ratios in soils investigated for enhanced C sequestration. Soil Biol. Biochem. 34, 997–1007. Bearden, B.N., Petersen, L., 2000. Influence of arbuscular mycorrhizal fungi on soil structure and aggregate stability of a Vertisol. Plant Soil 218, 173–183. Beare, M.H., Parmelee, R.W., Hendrix, P.F., Cheng, W., Coleman, D.C., Crossley Jr., D.A., 1992. Microbial and faunal interactions and effects on litter nitrogen and decomposition in agroecosystems. Ecol. Monogr. 62, 569–591. Blackwood, C.B., Dell, C.J., Smucker, A.J.M., Paul, E.A., 2006. Eubacterial communities in different soil macroaggregate environments and cropping systems. Soil Biol. Biochem. 38, 720–728. Bligh, E.G., Dyer, W.H., 1959. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917. Bossuyt, H., Denef, K., Six, J., Frey, S.D., Merckx, R., Paustian, K., 2001. Influence of microbial populations and residue quality on aggregate stability. Appl. Soil Ecol. 16, 195–208. Bossuyt, H., Six, J., Hendrix, P.F., 2002. Aggregate-protected carbon in no-tillage and conventional tillage agroecosystems using carbon-14 labeled plant residue. Soil Sci. Soc. Am. J. 66, 1965–1973. Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254. Chantigny, M.H., Angers, D.A., Prévost, D., Vézina, L.-P., Chalifour, F.-P., 1997. Soil aggregation and fungal and bacterial biomass under annual and perennial cropping systems. Soil Sci. Soc. Am. J. 61, 262–267. Drijber, R.A., Doran, J.W., Parkhurst, A.M., Lyon, D.J., 2000. Changes in soil microbial community structure with tillage under long-term wheat-fallow management. Soil Biol. Biochem. 32, 1419–1430. Elliott, E.T., Coleman, D.C., 1988. Let the soil work for us. Ecol. Bull. 39, 23–32. Elliott, E.T., Palm, C.A., Reuss, D.E., Monz, C.A., 1991. Organic matter contained in soil aggregates from a tropical chronosequence: correction for sand and light fraction. Agric. Ecosyst. Environ. 34, 443–451. Feng, Y., Motta, A.C., Reeves, D.W., Burmester, C.H., van Santen, E., Osborne, J.A., 2003. Soil microbial communities under conventional-till and no-till continuous cotton systems. Soil Biol. Biochem. 35, 1693–1703. Frey, S.D., Elliott, 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. Gale, W.J., Cambardella, C.A., Bailey, T.B., 2000. Root-derived carbon and the formation and stabilization of aggregates. Soil Sci. Soc. Am. J. 64, 201–207. Grogan, D.W., Cronan, J.E., 1997. Cyclopropane ring formation in membrane lipids of bacteria. Microbiol. Mol. Biol. Rev. 61, 429–441. Guggenberger, G., Frey, S.D., Six, J., Paustian, K., Elliott, E.T., 1999. Bacterial and fungal cell-wall residues in conventional and no-tillage agroecosystems. Soil Sci. Soc. Am. J. 63, 1188–1198. Gupta, V.V.S.R., Germida, J.J., 1988. Distribution of microbial biomass and its activity in different soil aggregate size classes as affected by cultivation. Soil Biol. Biochem. 20, 777–786. Hedrick, D.B., Peacock, A., White, D.C., 2005. Interpretation of fatty acid profiles of soil microorganisms. In: Margesin, R., Schinner, F. (Eds.), Manual for Soil Analysis—Monitoring and Assessing Soil Bioremediation. Springer-Verlag, Berlin, pp. 251–259.
Helgason, B.L., Walley, F.L., Germida, J.J., 2010. Long-term no-till management affects microbial biomass but not community composition in Canadian prairie agroecosystems. Soil Biol. Biochem. 42, 2192–2202. Helgason, B.L., Walley, F.L., Germida, J.J., 2009. Fungal and bacterial abundance in long-term no-till and intensive-till soils of the Northern Great Plains. Soil Sci. Soc. Am. J. 73, 120–127. Kabir, Z., O’Halloran, I.P., Hamel, C., 1999. Combined effects of soil disturbance and fallowing on plant and fungal components of mycorrhizal corn (Zea mays L.). Soil Biol. Biochem. 31, 307–314. Macdonald, L.M., Paterson, E., Dawson, L.A., McDonald, A.J.S., 2004. Short-term effects of defoliation on the soil microbial community associated with two contrasting Lolium perenne cultivars. Soil Biol. Biochem. 36, 489–498. Márquez, C.O., Garcia, V.J., Cambardella, C.A., Shultz, R.C., Isenhart, T.M., 2004. Aggregate-size stability distribution and soil stability. Soil Sci. Soc. Am. J. 68, 725–735. McCune, B., Grace, J.B., 2002. Analysis of Ecological Communities. MjM Software Design, Gleneden Beach, Oregon, USA. McGonigle, T.P., Millar, M.H., 1996. Development of fungi below ground in association with plants growing in disturbed and undisturbed soils. Soil Biol. Biochem. 28, 263–269. Mikha, M.M., Rice, C.W., 2004. Tillage and manure effects on soil aggregateassociated carbon and nitrogen. Soil Sci. Soc. Am. J. 68, 809–816. Minoshima, H., Jackson, L.E., Cavagnaro, T.R., Sánchez-Moreno, S., Ferris, H., Temple, S.R., Goyal, S., Mitchell, J.P., 2007. Soil food webs and carbon dynamics in response to conservation tillage in California. Soil Sci. Soc. Am. J. 71, 952–963. Muruganandam, S., Israel, D.W., Robarge, W.P., 2009. Activities of nitrogenmineralization enzymes associated with soil aggregate size fractions of three tillage systems. Soil Sci. Soc. Am. J. 73, 751–759. Muruganandam, S., Israel, D.W., Robarge, W.P., 2010. Nitrogen transformations and microbial communities in soil aggregates from three tillage systems. Soil Sci. Soc. Am. J. 74, 120–129. Oades, J.M., 1984. Soil organic matter and structural stability: mechanisms and implications for management. Plant Soil 76, 319–337. Olchin, G.P., Ogle, S., Frey, S.D., Filley, T.R., Paustian, K., Six, J., 2008. Residue carbon stabilization in soil aggregates of no-till and tillage management of dryland cropping systems. Soil Sci. Soc. Am. J. 72, 507–513. Olsson, P.A., 1999. Signature fatty acids provide tools for determination of the distribution and interactions of mycorrhizal fungi in soil. FEMS Microbiol. Ecol. 29, 303–310. Paradelo, R., Barral, M.T., 2009. Effect of moisture and disaggregation on the microbial activity of soil. Soil Tillage Res. 104, 317–319. Peixoto, R.S., Coutinho, H.L.C., Madari, B., Machado, P.L.O.A., Rumjanek, N.G., Van Elsas, J.D., Seldin, L., Rosado, A.S., 2006. Soil aggregation and bacterial community structure as affected by tillage and cover cropping in the Brazilian Cerrados. Soil Tillage Res. 90, 16–28. Pikul, J.L., Rice, G.C.J., Schumacher, A.E.T.E., Nichols, K., Johnson, J.M.F., Wright, S., Caesar, T., Ellsbury, M., 2009. Organic matter and water stability of field aggregates affected by tillage in South Dakota. Soil Sci. Soc. Am. J. 73, 197–206. Pinno, B.D., Belanger, N., 2008. Ecosystem carbon gains from afforestation in the Boreal Transition ecozone of Saskatchewan (Canada) are coupled with the devolution of Black Chernozems. Agric. Ecosyst. Environ. 12, 56–62. Plante, A.F., Six, J., Paul, E.A., Conant, R.T., 2009. Does physical protection of organic matter attenuate temperature sensitivity? Soil Sci. Soc. Am. J. 73, 1168–1172. Rillig, M.C., 2004. Arbuscular mycorrhizae, glomalin, and soil aggregation. Can. J. Soil Sci. 84, 355–363. Rosier, C.L., Hoye, A.T., Rillig, M.C., 2006. Glomalin-related soil protein: assessment of current detection and quantification tools. Soil Biol. Biochem. 38, 2205–2211. Sainju, U.M., 2006. Carbon and nitrogen pools in soil aggregates separated by dry and wet sieving methods. Soil Sci. 171, 937–949. Schutter, M.E., Dick, R.P., 2002. Microbial community profiles and activities among aggregates of winter fallow and cover-cropped soil. Soil Sci. Soc. Am. J. 66, 142–153. Simpson, R.T., Frey, S.D., Six, J., Thiet, R.K., 2004. Preferential accumulation of microbial carbon in aggregate structures of no-tillage soils. Soil Sci. Soc. Am. J. 68, 1249–1255. Six, J., Bossuyt, H., Degryze, S., Denef, K., 2004. A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res. 79, 7–31. Six, J., Elliott, E.T., Paustian, K., 1999. Aggregate and soil organic matter dynamics under conventional and no-tillage systems. Soil Sci. Soc. Am. J. 63, 1350–1358. Six, J., Elliott, E.T., Paustian, K., 2000. Soil macroaggregate turnover and microaggregate formation: a mechanism for C sequestration under no-tillage agriculture. Soil Biol. Biochem. 32, 2099–2103. Six, J., Elliott, E.T., Paustian, K., Doran, J.W., 1998. Aggregation and soil organic matter accumulation in cultivated and native grassland soils. Soil Sci. Soc. Am. J. 62, 1367–1377. Spedding, T.A., Hamel, C., Mehuys, G.R., Madramootoo, C.A., 2004. Soil microbial dynamics in maize-growing soil under different tillage and residue management systems. Soil Biol. Biochem. 36, 499–512. Tisdall, J.M., Oades, J.M., 1982. Organic matter and water-stable aggregates in soils. J. Soil Sci. 33, 141–163. Väisänen, R.K., Roberts, M.S., Garland, J.L., Frey, S.D., Dawson, L.A., 2005. Physiological and molecular characterisation of microbial communities associated with different water-stable aggregate size classes. Soil Biol. Biochem. 37, 2007–2016.
B.L. Helgason et al. / Applied Soil Ecology 46 (2010) 390–397 Wardle, D.A., 1995. Impacts of disturbance on detritus food webs in agro-ecosystems of contrasting tillage and weed management practices. Adv. Ecol. Res. 26, 105–185. White, D.C., Davis, W.M., Nickels, J.S., King, J.C., Bobbie, R.J., 1979. Determination of the sedimentary microbial biomass by extractable lipid phosphate. Oecologia 40, 51–62. White, P.M., Rice, C.W., 2009. Tillage effects on microbial and carbon dynamics during plant residue decomposition. Soil Sci. Soc. Am. J. 73, 138–145. Wilson, G.W.T., Rice, C.W., Rillig, M.C., Hartnett, D.C., 2009. Soil aggregation and carbon sequestration are tightly correlated with the abundance of arbuscular mycorrhizal fungi: results from long-term field experiments. Ecol. Lett. 12, 452–461. Wortmann, C.S., Quincke, J.A., Drijber, R.A., Mamo, M., Franti, T., 2008. Soil microbial community change and recovery after one-time tillage of continuous no-till. Agron. J. 100, 1681–1686. Wright, S.F., Franke-Snyder, M., Morton, J.B., Upadhyaya, A., 1996. Time-course study and partial characterization of a protein on hyphae of arbuscular mycorrhizal fungi during active colonization of roots. Plant Soil 181, 193–203. Wright, S.F., Green, V.S., Cavigelli, M.A., 2007. Glomalin in aggregate size classes from three different farming systems. Soil Tillage Res. 94, 546–549.
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Wright, A.L., Hons, F.M., 2005. Soil carbon and nitrogen storage in aggregates from different tillage and crop regimes. Soil Sci. Soc. Am. J. 69, 141–147. Wright, S.F., Starr, J.L., Paltineanu, I.C., 1999. Changes in aggregate stability and concentration of glomalin during tillage management transition. Soil Sci. Soc. Am. J. 63, 1825–1829. Wright, S.F., Upadhyaya, A., 1998. A survey of soils for aggregate stability and glomalin, a glycoprotein produced by hyphae of arbuscular mycorrhizal fungi. Plant Soil 198, 97–107. Yamashita, T., Flessa, H., John, B., Helfrich, M., Ludwig, B., 2006. Organic matter in density fractions of water-stable aggregates in silty soils: effect of land use. Soil Biol. Biochem. 38, 3222–3234. Young, I.M., Ritz, K., 2000. Tillage, habitat space and function of soil microbes. Soil Tillage Res. 53, 201–213. Zelles, L., Bai, Q.Y., Beck, T., Beese, F., 1992. Signature fatty acids in phospholipids and lipopolysaccharides as indicators of microbial biomass and community structure in agricultural soils. Soil Biol. Biochem. 24, 317–323. Zibilske, L.M., Bradford, J.M., 2007. Soil aggregation, aggregate carbon and nitrogen, and moisture retention induced by conservation tillage. Soil Sci. Soc. Am. J. 71, 793–802.
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Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil
No-till soil management increases microbial biomass and alters community profiles in soil aggregates B.L. Helgason a,∗ , F.L. Walley b , J.J. Germida b a b
Agriculture and Agri-Food Canada, Saskatoon Research Centre, 107 Science Place, Saskatoon, SK, S7N 0X2, Canada Department of Soil Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada
a r t i c l e
i n f o
Article history: Received 19 February 2010 Received in revised form 30 September 2010 Accepted 5 October 2010 Keywords: No-till Tillage Aggregates Microbial biomass Microbial community
a b s t r a c t Aggregation is important for soil functioning, providing physical protection of organic matter and microbial inhabitants. Tillage disrupts aggregates, increases wind and water erosion of soils and exposes formerly protected organic matter to decomposition and losses. Microbial biomass and community dynamics in dry-sieved aggregate-size classes from long-term no-till (NT) and conventionally tilled (CT) soils were examined using phospholipid fatty acid analysis (PLFA). Bacterial, fungal, and total biomass were up to 32% greater in NT compared to CT aggregates. Aggregate size also affected microbial biomass, which was highest in the 1–2 mm size class. Arbuscular mycorrhizal fungi (AMF) were particularly affected by tillage disturbance with increases of 40–60% among aggregate-size classes in NT vs. CT, but glomalin related soil protein concentration was not different between tillage treatments or among aggregate-size classes. Bacterial stress biomarkers were higher in CT than NT aggregates but were not significantly correlated with total C, total N or C:N ratio, indicating that the physiological status of bacteria within aggregates was not simply governed by the quantity of available resources. Ordination analysis of PLFA profiles demonstrated a shift in microbial community structure between NT and CT aggregates, correlated with AMF abundance in NT aggregates and increased bacterial stress biomarkers in CT aggregates. Our results demonstrated greater microbial biomass and altered microbial community structure in NT vs. CT aggregates. This work demonstrates that tillage management influences microbial community structure within aggregates and may provide a potential explanation for differences in process rates observed in NT vs. CT soils. Further research into the processes that govern community structure in aggregates from NT and tilled soils is needed to better understand how the interaction of microorganisms with their physical environment affects nutrient turnover and availability. Crown Copyright © 2010 Published by Elsevier B.V. All rights reserved.
1. Introduction Aggregation is an important facet of soil structure, providing resistance to wind and water erosion, physical protection of organic matter and microsites for microbial activity. Agroecosystem productivity and sustainability are dependent on the maintenance of key microbial processes. Aggregates provide habitat for microbial activity and understanding how management affects the distribution of microbial functional groups among aggregates will lead to a better understanding of the regulation of microbial processes including soil C storage, nutrient turnover and trace gas emissions. The primary mechanisms to influence soil microbial communities are through the alteration of soil structure or substrate inputs (i.e., crop residues) (Elliott and Coleman, 1988). In this way, soil biological activity and the physical soil environment are related
∗ Corresponding author. Tel.: +1 306 975 6510; fax: +1 306 966 4226. E-mail address: [email protected] (B.L. Helgason).
through dynamic feedback mechanisms which inextricably link these two primary foundations of soil functioning (Young and Ritz, 2000). Tillage affects soil aggregation directly through physical disruption, and indirectly through influences on the broader biological and chemical soil environment (Young and Ritz, 2000). Macroaggregate stability is especially susceptible to agronomic practices (Six et al., 2004). Macroaggregates are stabilized by plant roots and fungal hyphae, as well as by the byproducts of microbial metabolism (Tisdall and Oades, 1982) and they provide habitat for soil bacteria while spatially protecting organic matter. Tillage affects both the level of aggregation and the rate of aggregate turnover (Six et al., 1998). Disruption during tillage events releases particulate organic matter from macroaggregates and increases organic matter turnover (Six et al., 2000). As a result, slower macroaggregate turnover under NT has been suggested as a potential mechanism for increased C storage in NT soils (Six et al., 1999). The formation of microaggregates within macroag-
0929-1393/$ – see front matter. Crown Copyright © 2010 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2010.10.002
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gregates serves to protect stabile C whereas macroaggregates are more important for the storage of labile C (Six et al., 2000; Bossuyt et al., 2002; Mikha and Rice, 2004). Beare et al. (1992) concluded that fungi contribute more to the formation of aggregates in NT than CT soils and Six et al. (2000) proposed that stable microaggregate formation within macroaggregates is vital for C sequestration in NT soils. Microbial biomass, including that of saprotrophic fungi and AMF often increases under NT management (Helgason et al., 2009; Muruganandam et al., 2009; White and Rice, 2009). However, relatively little is known about the mechanisms that drive aggregate turnover and protect different forms of C within aggregates (Six et al., 2004; Abiven et al., 2009). Separation of aggregates into multiple size classes can by done in many ways (e.g., dry sieving fresh or air-dry soil as well as wet sieving of fresh or air-dry soil). The means by which the aggregates are obtained affects the way in which aggregates are both defined and potentially linked to function in the broader soil context (Ashman et al., 2009). It is common to assess water-stable aggregates (WSA) in the study of soil C dynamics (Six et al., 1999; Wright and Hons, 2005; Yamashita et al., 2006; Olchin et al., 2008; White and Rice, 2009) and the bulk of recent aggregate research has employed wet sieving of air-dried aggregates. However, it is clearly demonstrated that the method of aggregate separation affects the resulting distribution of aggregate sizes as well as their chemical (Sainju, 2006) and biological (Ashman et al., 2009; Paradelo and Barral, 2009) characteristics. Sainju (2006) compared aggregate separation methods and concluded that dry sieving moist soil can be used as a reliable method of separating aggregates. Dry sieving methods have previously been used in studies of microbiological properties of aggregates (Schutter and Dick, 2002; Muruganandam et al., 2009, 2010). Other studies of microbial communities directly associated with aggregates are few and most information regarding aggregate microbial communities is indirectly linked to the aggregates themselves by evaluation of bulk soil communities (e.g., Väisänen et al., 2005). Peixoto et al. (2006) examined 16S rRNA genes in NT vs. CT bulk soils and found that the NT community was more similar to that of an adjacent soil under forested vegetation than to the tilled soil which they attributed to changes in soil structure, including increased mean weight diameter of aggregates under NT. Muruganandam et al. (2010) recently found that microbial community composition differed between aggregates from NT and tilled soils, but were not different among aggregate-size classes. Schutter and Dick (2002) showed differences in aggregate FAME profiles as a function of sampling date and winter cover cropping, but to a lesser extent by aggregate size. Previous work in the same long-term NT and CT soils at Swift Current, SK, Canada, demonstrated an increase in total, bacterial and fungal biomass (Helgason et al., 2009), but not community structure (Helgason et al., 2010) in bulk soils. Given the enormous influence that soil heterogeneity can exert on microbially-mediated processes (Young and Ritz, 2000), aggregate microenvironments have the potential to greatly affect overall soil functioning. In this way, differences in soil functioning between CT and NT soils may be partially explained by differences in aggregate microhabitats. We hypothesized that because macroaggregates are particularly susceptible to physical disruption by tillage, shifts in microbial community structure may occur among naturally formed field aggregates in NT and CT soils. To test this hypothesis, we examined microbial communities in aggregates from a long-term experiment where physical disturbance from tillage intensity varied, but cropping system management was otherwise held constant. Phospholipid fatty acid analysis was used to evaluate the abundance and community structure of soil microorganisms in dry-sieved aggregate-size fractions from NT and CT soils.
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2. Materials and methods 2.1. Soil collection and aggregate isolation Aggregates were obtained from a long-term tillage experiment in a semi-arid prairie region at Swift Current, SK, Canada. The experiment is a randomized complete block design (n = 4) with individual plot sizes of 15.24 m × 32.00 m. The experiment was initiated in 1981 and is continuously cropped in a four-year rotation of wheat–lentil–wheat–pea. Tillage disturbance in the CT soils was relatively low, involving one pre-seeding pass with a heavy-duty cultivator and mounted harrows. Both CT and NT plots were seeded using an air-drill equipped with knife openers. Soils were sampled on April 27, 2006 (which followed a lentil crop in 2005), prior to seeding and any pre-seeding tillage disturbance in the CT plots. This sampling date was chosen to minimize the effect of in-season influences, including plant growth and fertilization. Samples (n = 10 per plot) were obtained using a hand trowel from the 0- to 10-cm depth and composited. Soil was stored on ice during transport back to the laboratory for processing. We chose to separate aggregates into five size classes through dry-sieving of fresh soil because both wet sieving and air drying compromised the in situ link between the aggregates obtained and their indigenous microbial inhabitants. Soil was initially passed through a 4-mm sieve. Naturally formed field aggregates (Pikul et al., 2009) were isolated manually by dry sieving 300 g of fresh soil (moisture content ca. 10%) on a series of 4 sieves (2 mm; 1 mm; 500 m, 250 m). Sieves were gently rotated 90 times at a rate of 30 rotations per minute in the following order: 30 rotations clockwise, 30 rotations counterclockwise followed by 15 rotations clockwise and 15 rotations counterclockwise. Aggregate distribution was determined by weight from each size class. This gentle sieving procedure aimed to minimize excessive disturbance of larger aggregates and was tested to ensure consistent and repeatable aggregate distribution in both NT and CT soils. No attempt was made to separate microaggregates from within macroaggregates and the aggregate-size classes chosen here primarily correspond to commonly defined macroaggregate fractions (i.e., >250 m) with only the smallest size fraction representing microaggregates. 2.2. General soil characteristics Gravimetric moisture content was determined by measuring moisture loss from fresh soil by mass after drying at 105 ◦ C for 48 h. Aggregate sand content (50–500 m particles) was determined following dispersal and sonication (Pinno and Belanger, 2008) by laser scattering particle-size analysis (using a Partic LA-950 (Horiba, Inc., Kyoto, Japan). Total C (TC) and total N (TN) were measured by dry combustion using a LECO CNS-2000 analyzer (LECO Instruments, Ltd., St. Joseph, MI). 2.3. Phospholipid fatty acid analysis PLFA was performed using the modified method of White et al. (1979), based on the original method of Bligh and Dyer (1959). Briefly, fatty acids were extracted from 4.0 g of lyophilized, ground soil using a single phase chloroform, methanol, phosphate buffer solution. Fatty acids were separated on a solid phase extraction column (0.50 g Si; Varian Inc., Mississauga, ON), phospholipids were methylated and resulting fatty acid methyl esters were analyzed using a Hewlett Packard 5890 Series II gas chromatograph with a 25 m Ultra 2 column (J&W Scientific). Peaks were identified using fatty acid standards and MIDI identification software (MIDI Inc., Newark, DE) and quantified based on the addition of internal standard methyl nonadecanoate (19:0). Total biomass was calculated as the sum of all identified PLFA peaks (Zelles et al., 1992). Rela-
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tive fungal and bacterial biomass in NT and CT soils was assessed using the fungal biomarker 18:26,9 and the sum of 13 bacterial biomarkers (i14:0, i15:0, a15:0, i16:0, 16:17c, 10Me16:0, i17:0, a17:0, cy17:0, 10Me17:0, 18:17, 10Me18:0, cy19:0) (Bååth and Anderson, 2003). Biomarkers used to represent gram positive bacteria (Gr+) were i14:0, i15:0, a15:0, i16:0, i17:0, a17:0 (Hedrick et al., 2005). Biomarkers used for gram negative bacteria (Gr−) were 16:17t, 16:19c, 16:17c, 18:17c, 18:19c, cy17:0, and cy19:0 (Macdonald et al., 2004). Biomass of AMF was evaluated using the PLFA biomarker 16:15c (Olsson, 1999). Physiological stress biomarkers denoted as Stress 1 and Stress 2 represent the ratios of cy17:0 to 16:17c and cy19:0 to 18:17c, respectively (Grogan and Cronan, 1997). 2.4. Glomalin extraction and quantification Easily extractable glomalin-related soil protein (GRSP) was obtained by extracting 1.0 g of soil in 8 mL of 20 mM sodium citrate buffer (pH 7.0) and autoclaving for 30 min at 121 ◦ C. Following extraction, soil was pelleted by centrifugation at 5000 × g for 15 min and the volume of supernatant measured. Glomalin related soil protein was measured (n = 2) using the Bradford total protein assay using bovine serum albumen as a standard (Bradford, 1976; Wright et al., 1996). 2.5. Statistical analysis Analysis of variance and correlation analyses were performed using SPSS version 13.0 for Windows (SPSS Inc., 2004). Prior to analysis, PLFA data were transformed using the log(mol% + 1) transformation but are presented here as untransformed data. Homogeneity of variance was assessed using Levine’s test. Relationships between soil characteristics, GRSP and PLFA biomarkers were assessed using Pearson’s correlation coefficient. Non-metric multidimensional scaling (MDS) using the Sørensen distance measure was carried out in the Autopilot Slow and Thorough analysis option in PCOrd V.5.0 (McCune and Grace, 2002). A random starting point was used for initial analysis in which stress was minimized. A starting configuration for the final ordination was then supplied from the least-stress solution obtained initially. Significance testing was performed using Monte Carlo analysis. A multi-response permutation procedure (MRPP) was performed using the Sørensen distance measure to test for differences between a priori groups and was carried out in PCOrd V.5.0.
3. Results and discussion Aggregates were separated using dry sieving and the proportional distribution by mass of different sized aggregates for NT and CT soils is listed in Table 1. Sand content of the aggregates ranged from 35 to 47% and was significantly (P < 0.07) greater in NT than CT as well as different among aggregate sizes (P < 0.001) (Table 1). Total C and TN, PLFA and GRSP data were adjusted for sand content to account for differences that result from physical sorting of nonaggregate associated sand particles (Elliott et al., 1991) and have been presented on a sand-free soil dry weight basis. Tillage interacted with aggregate size (P < 0.08) to affect the mass distribution of aggregates. There were more macroaggregates in NT than CT, except in the 1–2 mm size class (Table 1). This is in agreement with other studies that examined water-stable macroaggregates in NT vs. CT soils (Wright and Hons, 2005; Zibilske and Bradford, 2007; Alvarez and Steinbach, 2009) but is in contrast to a recent study of dry-sieved aggregates by Muruganandam et al. (2009) who found no effect of tillage on aggregate distribution. No-till aggregates had significantly higher TC (P < 0.06) and TN (P < 0.04) than CT aggregates, but C:N ratio did not differ significantly as a function of tillage (Table 1). Earlier work demonstrated that there was no significant difference in TC or TN content between NT and CT in bulk soils (not expressed on a sand-free basis) (Helgason et al., 2009). However, C to N ratio was lower in NT bulk soils, as was the non-significant trend with NT aggregates (Table 1) which may indicate differences in substrate chemistry within NT and CT aggregates. There was no significant difference in TC, TN or C:N ratio among aggregate-size classes. Total, bacterial and fungal biomass were greater in NT than CT aggregates and varied significantly among different aggregate-size classes (Fig. 1; Table 2). While biomass differed among tillage treatments, the relative abundance of bacteria and fungi (i.e., proportion of the total community, expressed as mol% of total PLFA) were not different between NT and CT aggregates. Increased microbial biomass is commonly found in NT vs. CT soils (Frey et al., 1999; Drijber et al., 2000; Bailey et al., 2002; Feng et al., 2003; Spedding et al., 2004; Minoshima et al., 2007; White and Rice, 2009) and was previously measured in the bulk soil (0–5 cm) at this experimental site (Helgason et al., 2009). Muruganandam et al. (2010) found greater relative abundance of fungi in NT aggregates which was positively correlated with the activity of various enzymes associated with N mineralization, linking increased fungal abundance to soil functioning. A second study (Muruganandam et al., 2010) demonstrated that increased microbial biomass, rather than altered community composition resulted in greater N transformation rates.
Table 1 Treatment means (n = 4) and analysis of variance (ANOVA) for moisture content, aggregate size distribution and sand content of different no-till (NT) and conventional-till (CT) aggregates expressed as a percent of the total sample (dry weight basis). Tillage
Aggregate size
Soil moisture (g kg−1 )
Aggregate distribution (%)
Sand content (%)
Total Ca (g kg−1 )
Total Na (g kg−1 )
C:N
NT CT NT CT NT CT NT CT NT CT
2–4 mm
113 98 109 98 111 101 104 99 86 8.3
36.0 30.6 15.4 17.5 20.3 19.7 16.8 15.5 11.6 16.7
38.3 33.5 41.5 39.5 36.5 35.0 40.5 36.5 46.5 37.8
29.6 27.1 33.4 30.7 29.5 27.7 30.4 27.6 30.3 28.2
3.56 3.07 3.79 3.47 3.41 3.12 3.66 3.17 3.63 2.87
8.43 8.95 9.00 9.08 8.79 9.08 8.46 8.87 8.57 9.85
ANOVA
Tillage (T) Aggregate size (A) TxA
P < 0.017 P < 0.003 P < 0.813
P < 0.908 P < 0.000 P < 0.078
P < 0.070 P < 0.002 P < 0.948
P < 0.065 P < 0.297 P < 0.997
P < 0.040 P < 0.798 P < 0.966
P < 0.252 P < 0.925 P < 0.938
a
1–2 mm 500 m to 1 mm 250–500 m <250 m
Data presented on a sand-free basis.
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Table 2 Analysis of variance (ANOVA) probability values for bacterial, fungal, total and fungal:bacterial ratio (F:B) of PLFA biomarkers in dry-sieved aggregates from long-term no-till (NT) and conventional-till (CT) soils at Swift Current, Saskatchewan, Canada. a
Tillage (T) Aggregate size (A) TxA a
a
Bacterial PLFA
a
Fungal PLFA
Total PLFA
nmol g−1 soil
mol%
nmol g−1 soil
mol%
nmol g−1 soil
0.000 0.025 0.447
0.318 0.001 0.910
0.001 0.000 0.093
0.722 0.000 0.813
0.000 0.036 0.442
F:B
0.628 0.000 0.789
Data presented on a sand-free basis.
Indirect evidence suggests microbial functional groups differentially inhabit and control aggregate-size fractions. Larger aggregates had a higher ratio of fungal:bacterial (F:B) biomass and a greater (P < 0.001) relative abundance of fungi, which is in agreement with aggregate formation theory (Six et al., 2004). Simpson et al. (2004) measured greater amino sugar C in WSA of NT over CT soils, indicating that more microbial-derived C is stored in aggregates in NT soils. Guggenberger et al. (1999) found that glucosamine, a fungal-derived amino sugar, accumulated in aggregates of NT soils which coincided with higher fungal biomass in the bulk soil. The current study relates fungal and bacterial biomass directly with aggregates of different sizes and shows that the F:B biomass ratio decreases with decreasing aggregate size. Fungi and roots are involved in macroaggregate formation, physically binding soil particles (Tisdall and Oades, 1982; Oades, 1984; Gupta and Germida, 1988; Chantigny et al., 1997; Bossuyt et al., 2001). Decreasing relative abundance of fungi vs. bacteria with decreasing aggregate size is consistent with this mechanism of aggregate formation. It is interesting to note that similar to the bulk soil (Helgason et al., 2009), while both fungal and bacterial biomass were greater in NT aggregates, there was no significant difference in the ratio of fungi vs. bacteria. Based on the research of Simpson et al. (2004) and Guggenberger et al. (1999), it seems fungi confer
greater influence on aggregate stability in NT than CT soils due to the greater overall abundance of fungal cell wall residues as a result of their recalcitrance, rather than a proportional increase in fungal biomass, at the expense of bacteria. Similar to total bacterial biomass, biomass of Gr+ and Gr- was higher in NT than CT aggregates and was greatest in the 1–2-mm aggregate-size fraction (Table 3). The relative abundance (mol %) of Gr+ and Gr− bacterial PLFA was not affected by either tillage or aggregate size (Table 3). These results are similar to the findings of Muruganandam et al. (2009) who found no effect of tillage on relative abundance of Gr+ or Gr− biomarkers in aggregates. Physiological stress biomarkers were significantly higher (P < 0.05) in CT aggregates but were not different among aggregatesize classes (Table 3). These stress biomarkers were correlated with microbial PLFA profiles in CT aggregates and with the functional group biomarkers in both NT and CT aggregates but not with TC, TN, or C:N ratio which were greater in NT than CT aggregates, indicating that it was not simply the overall quantities of C and N that affected community structure. Organic matter distribution is known to differ between aggregate size fractions from NT and CT soils (Six et al., 1999). Further investigation of the link between community structure and the chemistry of C and N resources within aggregates is needed. A recent study by Plante et al. (2009) found increased respi-
Fig. 1. Bacterial and fungal PLFA biomarkers (sand-free basis), total PLFA extracted and fungal:bacterial (F:B) PLFA ratio in aggregates from long-term no-till (NT) and conventional-till (CT) soils. Error bars represent standard deviations (n = 4).
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Table 3 Treatment means and analysis of variance (ANOVA) for absolute and relative quantity of gram positive (Gr+), gram negative (Gr−) bacterial and stress PLFA biomarkers and glomalin related soil protein in aggregates from long-term NT and CT soils. Tillage
Aggregate size
Gr+ (nmol g−1 soil)
Gr− (nmol g−1 soil)
Gr+ (mol%)
Gr− (mol%)
Stress 1
Stress 2
a
NT CT NT CT NT CT NT CT NT CT
2–4 mm
14.0 11.9 17.7 12.1 14.8 11.2 14.7 10.7 14.0 10.7
15.5 14.2 21.3 14.7 17.1 13.2 16.9 13.5 15.8 12.6
21.8 20.7 20.7 20.7 21.2 20.9 21.6 20.4 21.4 20.8
21.4 24.6 24.8 25.2 24.3 24.7 24.9 25.6 24.4 25.1
0.265 0.347 0.246 0.352 0.260 0.364 0.260 0.362 0.240 0.337
0.206 0.259 0.211 0.288 0.198 0.219 0.169 0.226 0.175 0.205
1.13 1.00 1.16 1.12 1.12 1.06 0.99 1.05 1.01 1.08
ANOVA
Tillage (T) Aggregate size (A) TxA
P < 0.000 P < 0.043 P < 0.361
P < 0.000 P < 0.015 P < 0.222
P < 0.159 P < 0.754 P < 0.735
P < 0.088 P < 0.397 P < 0.998
P < 0.000 P < 0.866 P < 0.990
P < 0.006 P < 0.137 P < 0.817
P < 0.187 P < 0.130 P < 0.740
a
1–2 mm 500 m to 1 mm 250–500 m <250 m
GRSP (mg g−1 )
Data presented on a sand-free basis.
ration rates from aggregates incubated under elevated temperature were attributable to increased microbial biomass. Differences in specific respiration rates in their study suggested microbial community composition rather than simple biomass measures needs to be assessed to understand the processes governing microbial substrate utilization within aggregates. Saprotrophic fungi and AMF produce abundant hyphae in soil and contribute to the formation of macroaggregates (Tisdall and Oades, 1982). Biomass of AMF was significantly greater (P < 0.001) in NT vs. CT (Fig. 2). In four out of five size classes, the AMF biomarker was 40–60% higher and in the 1–2 mm size class the AMF biomarker was 2-fold greater in NT than CT, indicating a strong effect of tillage disturbance. Relative abundance of AMF was also significantly higher (P < 0.001) in NT than CT aggregates (not shown). Fungal biomass decreased with aggregate size (Fig. 1), whereas AMF biomass remained constant among the three smallest size classes (Fig. 2) resulting in a ratio of AMF:fungi that was inversely related to aggregate size (Fig. 3). This suggests that AMF may be exploiting a spatial niche within small aggregates that saprotrophic fungi are either less able or less apt to explore. Both saprotrophic and AMF hyphae are sensitive to physical disruption by tillage (Elliott and Coleman, 1988; Wardle, 1995). Decreased AMF hyphal length and inoculum potential as a result of physical soil disturbance has been clearly demonstrated (McGonigle and Millar, 1996; Kabir et al., 1999). Wortmann et al. (2008) found a slower recovery of AMF than other microbial groups following a one time tillage event in long-term NT soils, indicating that AMF may be particularly susceptible to tillage stress.
An indirect, but potentially important role of AMF contribution to macroaggregate formation occurs through promotion of root growth (Bearden and Petersen, 2000). Roots bind soil particles, release exudates and provide particulate organic matter that facilitates aggregate formation and stability (Tisdall and Oades, 1982; Gale et al., 2000; Márquez et al., 2004; Six et al., 2004). This dominance of AMF in NT aggregates agrees with Wilson et al. (2009) who found that AMF biomass was a remarkably good predictor of soil aggregation in grassland soils. Glomalin, an abundant proteinaceous material in soil, coats the surfaces of hyphae and soil particles (Wright et al., 2007) and is thought to confer water-stability to aggregates by acting as a binding agent. While the origin of glomalin remains unproven (Rillig, 2004; Rosier et al., 2006), it is circumstantially linked to AMF and has a relatively long turnover time, far longer than hyphae. In our study, easily extractable GRSP did not differ among tillage treatments or aggregate fractions (Table 3). Correlation between GRSP and AMF biomass was good in CT aggregates (r = 0.76), but there was no relationship in NT aggregates (r = 0.04). In grassland soils subjected to various stresses, Wilson et al. (2009) found a continuous linear relationship between AMF biomass and aggregation (WSA). Importantly, they did not detect a threshold above which AMF abundance ceased to affect aggregation. It is possible that the lack of positive correlation seen here in the NT aggregates could have been caused by a change in growth pattern of the AMF. Biomass of AMF was measured using the PLFA biomarker 16:15c which is present in hyphae and spores. Because glomalin is deposited in
NT NT IT CT
7
4.0
-1
AMF PLFA biomarker -1 (nmol g soil)
8
AMF PLFA (nmol g soil)
5.0
9
6 5 4 3 2 1
3.0
2.0
1.0
NT 2-4mm NT 250um-0.5mm CT 1-2mm CT <250um
0 2-4mm
1-2mm
500µm1mm
250µm500µm
<250µm
Aggregate size class Fig. 2. Arbuscular mycorrhizal fungi (AMF) PLFA biomarker (sand-free basis) in aggregates from long-term no-till (NT) and conventional-till (CT) soils. Error bars represent standard deviations (n = 4).
0.0 0.0
1.0
NT 1-2mm NT <250um CT 500um-1mm
2.0
NT 500um-1mm CT 2-4mm CT 250-500um
3.0
4.0
5.0
-1
Fungal PLFA(nmol g soil) Fig. 3. Relationship between fungal (18:2w6,9) and arbuscular mycorrhizal fungi (AMF) (16:15c) biomarkers in aggregates from long-term no-till (NT) and conventional-till (CT) soils.
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Axis 2 (35%)
AMF hyphal walls, a significant increase in sporulation without an increase in hyphal growth could decouple the relationship between AMF biomarker and GRSP. Wright et al. (1999) showed a strong linear relationship between GRSP and aggregate stability in soils transitioning from CT to NT and that GRSP was highly correlated with water-stable aggregation (measured in the 1–2 mm size class) across a wide range of soils (Wright and Upadhyaya, 1998). A more recent paper (Wright et al., 2007) reported that GRSP increased as water-stable aggregate size increased in NT soils, but remained constant across aggregatesize classes in disturbed soils (including a CT treatment). In the present study of dry-sieved aggregates, GRSP did not change significantly among aggregate-size classes in either tillage treatment. The lack of relationship between dry-sieved aggregate-size distribution and GRSP seen here supports the theory proposed by Wright et al. (2007) that glomalin acts as a microbial glue and of Wilson et al. (2009) that AMF are instrumental in binding microaggregates together into macroaggregates. Analysis of PLFA profiles using MDS ordination resulted in a 3dimensional solution with a final stress of 12.0 (instability = 0.000) and accounted for 90% of the variability in the data set. Tillage man-
STRESS 1 CT
NT AMF
4. Conclusions
MRPP Tillage Axis 3 (37%)
agement separated communities along Axis 2 and to some extent along Axis 1 (Fig. 4). Microbial stress biomarkers were positively correlated with CT aggregate profiles, while the AMF biomarker was correlated with NT aggregates indicating that physiological stress (e.g., moisture or nutrient limitation) was influential in determining overall community structure in CT aggregates and AMF were influential in NT aggregate communities. It is interesting that ordination analysis of the entire lipid profile separated NT and CT soils, but that the relative abundance (mol%) of microbial biomarkers for different functional groups was not different between tillage treatments. This indicates that the tillage-induced differentiation within the community occurs at a level of organization more complex than broad groupings indicated by PLFA biomarkers. Blackwood et al. (2006) found little difference in bacterial T-RFLP profiles or cell counts between aggregate interiors and exteriors. However, they found greater bacterial biovolume in aggregate interiors. Thus, activity but not cell number, was correlated with C content of the aggregates suggesting that bacterial activity may be related to C concentration. In the present study, community PLFA profiles also differed among aggregate-size classes, in contrast with the findings of Schutter and Dick (2002) who found a minimal influence of aggregate size on community FAME profiles. They speculated that this lack of difference in aggregate community structure was due to the redistribution of organisms among aggregates during tillage. In our study, physical soil disturbance is minimal even in the CT treatment, negating this potential smoothing effect on community structure among aggregate sizes.
STRESS 2
Axis 1 (18%)
A = 0.063 STRESS 2
STRESS 1 CT
P < 0.001 Aggregate size
AMF
A = 0.040
NT
P < 0.007 Final stress 12.0
Axis 2 (35%)
Axis 3 (37%)
395
STRESS 1
STRESS 2 CT AMF NT
Axis 1 (18%)
NT 2-4mm
NT 1-2mm
NT 0.5-1mm
NT 250-500um
CT 2-4mm
CT 1-2mm
CT 0.5-1mm
CT 250-500um
NT <250um CT <250um Fig. 4. Two-dimensional depiction of the three-dimensional non-metric multidimensional scaling (MDS) ordination analysis and multiple response permutation procedure (MRPP) of PLFA profiles from aggregates (final stress = 12.0) in no-till (NT) and conventional-till (CT) soils.
Tillage treatments affected microbial biomass and community structure in aggregates of semi-arid prairie soils. Total microbial biomass, as well as biomass of functional groups, was greater in NT vs. CT aggregates but the relative abundance of different functional groups was not affected by tillage (except for AMF). Ordination analysis of PLFA profiles showed that community structure shifted as a function of tillage, demonstrating a response to changing conditions in aggregates in NT soils at a finer scale than could be detected by functional group biomarkers. Elimination of tillage disturbance promoted AMF, with significant increases in total and relative abundance of AMF in NT aggregates. Given recent evidence of the importance of AMF for soil aggregation (e.g., Wilson et al., 2009) and the stabilization and sequestration of C, promotion of AMF by reducing tillage disturbance is beneficial for sustainable management of agroecosystems. Tillage-induced changes in aggregate microbial community structure observed here were not detected in bulk soils from the same site (Helgason et al., 2010), highlighting the value of studying microbial communities at additional spatial scales. Tillage-induced differences within aggregates may lead to changes in microbial functioning as a possible explanation for differences in crop growth in NT vs. CT soils. While this variation in community structure was demonstrated prior to seeding, a temporal comparison of microbial community dynamics during the growing season would help to determine whether these differences diverge or converge as crop development proceeds and may further explain crop growth and yield characteristics. Further research is needed on the relationship of tillage with microbial community structure and function across aggregate-size fractions. Microscale physical and biological changes in NT and CT soils are not well understood. In order to elucidate how tillage influences soil processes, a more detailed understanding of finescale interactions is needed. Differences in C storage potential exist in NT and CT aggregates, but relatively little is understood about the mechanisms that facilitate C preservation. Relating the chem-
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ical composition of C and N resources within aggregates directly to microbial biomass and community structure is necessary to enhance our understanding of the mechanisms of C storage and nutrient turnover in NT soils. Acknowledgements The authors wish to thank Dr. B. McConkey at the AAFC Swift Current Research Station and Dr. S. Brant at the AAFC Scott Research Station as well as the University of Alberta and Alberta Agriculture and Food for providing access to the long-term tillage trials studied. Technical assistance from Morgan Sather and Corrie Kosty is gratefully acknowledged. This research was supported by Agriculture and Agri-Food Canada and Natural Sciences and Engineering Research Council of Canada (NSERC). References Abiven, S., Menasseri, S., Chenu, C., 2009. The effects of organic inputs over time on soil aggregate stability—a literature analysis. Soil Biol. Biochem. 41, 1–12. Alvarez, R., Steinbach, H.S., 2009. A review of the effects of tillage systems on some soil physical properties, water content, nitrate availability and crops yield in the Argentine Pampas. Soil Tillage Res. 104, 1–15. Ashman, M.R., Hallett, P.D., Brookes, P.C., Allen, J., 2009. Evaluating soil stabilization by biological processes using step-wise aggregate fractionation. Soil Tillage Res. 102, 209–215. Bååth, 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. Bailey, V.L., Smith, J.L., Bolton Jr., H., 2002. Fungal-to-bacterial ratios in soils investigated for enhanced C sequestration. Soil Biol. Biochem. 34, 997–1007. Bearden, B.N., Petersen, L., 2000. Influence of arbuscular mycorrhizal fungi on soil structure and aggregate stability of a Vertisol. Plant Soil 218, 173–183. Beare, M.H., Parmelee, R.W., Hendrix, P.F., Cheng, W., Coleman, D.C., Crossley Jr., D.A., 1992. Microbial and faunal interactions and effects on litter nitrogen and decomposition in agroecosystems. Ecol. Monogr. 62, 569–591. Blackwood, C.B., Dell, C.J., Smucker, A.J.M., Paul, E.A., 2006. Eubacterial communities in different soil macroaggregate environments and cropping systems. Soil Biol. Biochem. 38, 720–728. Bligh, E.G., Dyer, W.H., 1959. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917. Bossuyt, H., Denef, K., Six, J., Frey, S.D., Merckx, R., Paustian, K., 2001. Influence of microbial populations and residue quality on aggregate stability. Appl. Soil Ecol. 16, 195–208. Bossuyt, H., Six, J., Hendrix, P.F., 2002. Aggregate-protected carbon in no-tillage and conventional tillage agroecosystems using carbon-14 labeled plant residue. Soil Sci. Soc. Am. J. 66, 1965–1973. Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254. Chantigny, M.H., Angers, D.A., Prévost, D., Vézina, L.-P., Chalifour, F.-P., 1997. Soil aggregation and fungal and bacterial biomass under annual and perennial cropping systems. Soil Sci. Soc. Am. J. 61, 262–267. Drijber, R.A., Doran, J.W., Parkhurst, A.M., Lyon, D.J., 2000. Changes in soil microbial community structure with tillage under long-term wheat-fallow management. Soil Biol. Biochem. 32, 1419–1430. Elliott, E.T., Coleman, D.C., 1988. Let the soil work for us. Ecol. Bull. 39, 23–32. Elliott, E.T., Palm, C.A., Reuss, D.E., Monz, C.A., 1991. Organic matter contained in soil aggregates from a tropical chronosequence: correction for sand and light fraction. Agric. Ecosyst. Environ. 34, 443–451. Feng, Y., Motta, A.C., Reeves, D.W., Burmester, C.H., van Santen, E., Osborne, J.A., 2003. Soil microbial communities under conventional-till and no-till continuous cotton systems. Soil Biol. Biochem. 35, 1693–1703. Frey, S.D., Elliott, 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. Gale, W.J., Cambardella, C.A., Bailey, T.B., 2000. Root-derived carbon and the formation and stabilization of aggregates. Soil Sci. Soc. Am. J. 64, 201–207. Grogan, D.W., Cronan, J.E., 1997. Cyclopropane ring formation in membrane lipids of bacteria. Microbiol. Mol. Biol. Rev. 61, 429–441. Guggenberger, G., Frey, S.D., Six, J., Paustian, K., Elliott, E.T., 1999. Bacterial and fungal cell-wall residues in conventional and no-tillage agroecosystems. Soil Sci. Soc. Am. J. 63, 1188–1198. Gupta, V.V.S.R., Germida, J.J., 1988. Distribution of microbial biomass and its activity in different soil aggregate size classes as affected by cultivation. Soil Biol. Biochem. 20, 777–786. Hedrick, D.B., Peacock, A., White, D.C., 2005. Interpretation of fatty acid profiles of soil microorganisms. In: Margesin, R., Schinner, F. (Eds.), Manual for Soil Analysis—Monitoring and Assessing Soil Bioremediation. Springer-Verlag, Berlin, pp. 251–259.
Helgason, B.L., Walley, F.L., Germida, J.J., 2010. Long-term no-till management affects microbial biomass but not community composition in Canadian prairie agroecosystems. Soil Biol. Biochem. 42, 2192–2202. Helgason, B.L., Walley, F.L., Germida, J.J., 2009. Fungal and bacterial abundance in long-term no-till and intensive-till soils of the Northern Great Plains. Soil Sci. Soc. Am. J. 73, 120–127. Kabir, Z., O’Halloran, I.P., Hamel, C., 1999. Combined effects of soil disturbance and fallowing on plant and fungal components of mycorrhizal corn (Zea mays L.). Soil Biol. Biochem. 31, 307–314. Macdonald, L.M., Paterson, E., Dawson, L.A., McDonald, A.J.S., 2004. Short-term effects of defoliation on the soil microbial community associated with two contrasting Lolium perenne cultivars. Soil Biol. Biochem. 36, 489–498. Márquez, C.O., Garcia, V.J., Cambardella, C.A., Shultz, R.C., Isenhart, T.M., 2004. Aggregate-size stability distribution and soil stability. Soil Sci. Soc. Am. J. 68, 725–735. McCune, B., Grace, J.B., 2002. Analysis of Ecological Communities. MjM Software Design, Gleneden Beach, Oregon, USA. McGonigle, T.P., Millar, M.H., 1996. Development of fungi below ground in association with plants growing in disturbed and undisturbed soils. Soil Biol. Biochem. 28, 263–269. Mikha, M.M., Rice, C.W., 2004. Tillage and manure effects on soil aggregateassociated carbon and nitrogen. Soil Sci. Soc. Am. J. 68, 809–816. Minoshima, H., Jackson, L.E., Cavagnaro, T.R., Sánchez-Moreno, S., Ferris, H., Temple, S.R., Goyal, S., Mitchell, J.P., 2007. Soil food webs and carbon dynamics in response to conservation tillage in California. Soil Sci. Soc. Am. J. 71, 952–963. Muruganandam, S., Israel, D.W., Robarge, W.P., 2009. Activities of nitrogenmineralization enzymes associated with soil aggregate size fractions of three tillage systems. Soil Sci. Soc. Am. J. 73, 751–759. Muruganandam, S., Israel, D.W., Robarge, W.P., 2010. Nitrogen transformations and microbial communities in soil aggregates from three tillage systems. Soil Sci. Soc. Am. J. 74, 120–129. Oades, J.M., 1984. Soil organic matter and structural stability: mechanisms and implications for management. Plant Soil 76, 319–337. Olchin, G.P., Ogle, S., Frey, S.D., Filley, T.R., Paustian, K., Six, J., 2008. Residue carbon stabilization in soil aggregates of no-till and tillage management of dryland cropping systems. Soil Sci. Soc. Am. J. 72, 507–513. Olsson, P.A., 1999. Signature fatty acids provide tools for determination of the distribution and interactions of mycorrhizal fungi in soil. FEMS Microbiol. Ecol. 29, 303–310. Paradelo, R., Barral, M.T., 2009. Effect of moisture and disaggregation on the microbial activity of soil. Soil Tillage Res. 104, 317–319. Peixoto, R.S., Coutinho, H.L.C., Madari, B., Machado, P.L.O.A., Rumjanek, N.G., Van Elsas, J.D., Seldin, L., Rosado, A.S., 2006. Soil aggregation and bacterial community structure as affected by tillage and cover cropping in the Brazilian Cerrados. Soil Tillage Res. 90, 16–28. Pikul, J.L., Rice, G.C.J., Schumacher, A.E.T.E., Nichols, K., Johnson, J.M.F., Wright, S., Caesar, T., Ellsbury, M., 2009. Organic matter and water stability of field aggregates affected by tillage in South Dakota. Soil Sci. Soc. Am. J. 73, 197–206. Pinno, B.D., Belanger, N., 2008. Ecosystem carbon gains from afforestation in the Boreal Transition ecozone of Saskatchewan (Canada) are coupled with the devolution of Black Chernozems. Agric. Ecosyst. Environ. 12, 56–62. Plante, A.F., Six, J., Paul, E.A., Conant, R.T., 2009. Does physical protection of organic matter attenuate temperature sensitivity? Soil Sci. Soc. Am. J. 73, 1168–1172. Rillig, M.C., 2004. Arbuscular mycorrhizae, glomalin, and soil aggregation. Can. J. Soil Sci. 84, 355–363. Rosier, C.L., Hoye, A.T., Rillig, M.C., 2006. Glomalin-related soil protein: assessment of current detection and quantification tools. Soil Biol. Biochem. 38, 2205–2211. Sainju, U.M., 2006. Carbon and nitrogen pools in soil aggregates separated by dry and wet sieving methods. Soil Sci. 171, 937–949. Schutter, M.E., Dick, R.P., 2002. Microbial community profiles and activities among aggregates of winter fallow and cover-cropped soil. Soil Sci. Soc. Am. J. 66, 142–153. Simpson, R.T., Frey, S.D., Six, J., Thiet, R.K., 2004. Preferential accumulation of microbial carbon in aggregate structures of no-tillage soils. Soil Sci. Soc. Am. J. 68, 1249–1255. Six, J., Bossuyt, H., Degryze, S., Denef, K., 2004. A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res. 79, 7–31. Six, J., Elliott, E.T., Paustian, K., 1999. Aggregate and soil organic matter dynamics under conventional and no-tillage systems. Soil Sci. Soc. Am. J. 63, 1350–1358. Six, J., Elliott, E.T., Paustian, K., 2000. Soil macroaggregate turnover and microaggregate formation: a mechanism for C sequestration under no-tillage agriculture. Soil Biol. Biochem. 32, 2099–2103. Six, J., Elliott, E.T., Paustian, K., Doran, J.W., 1998. Aggregation and soil organic matter accumulation in cultivated and native grassland soils. Soil Sci. Soc. Am. J. 62, 1367–1377. Spedding, T.A., Hamel, C., Mehuys, G.R., Madramootoo, C.A., 2004. Soil microbial dynamics in maize-growing soil under different tillage and residue management systems. Soil Biol. Biochem. 36, 499–512. Tisdall, J.M., Oades, J.M., 1982. Organic matter and water-stable aggregates in soils. J. Soil Sci. 33, 141–163. Väisänen, R.K., Roberts, M.S., Garland, J.L., Frey, S.D., Dawson, L.A., 2005. Physiological and molecular characterisation of microbial communities associated with different water-stable aggregate size classes. Soil Biol. Biochem. 37, 2007–2016.
B.L. Helgason et al. / Applied Soil Ecology 46 (2010) 390–397 Wardle, D.A., 1995. Impacts of disturbance on detritus food webs in agro-ecosystems of contrasting tillage and weed management practices. Adv. Ecol. Res. 26, 105–185. White, D.C., Davis, W.M., Nickels, J.S., King, J.C., Bobbie, R.J., 1979. Determination of the sedimentary microbial biomass by extractable lipid phosphate. Oecologia 40, 51–62. White, P.M., Rice, C.W., 2009. Tillage effects on microbial and carbon dynamics during plant residue decomposition. Soil Sci. Soc. Am. J. 73, 138–145. Wilson, G.W.T., Rice, C.W., Rillig, M.C., Hartnett, D.C., 2009. Soil aggregation and carbon sequestration are tightly correlated with the abundance of arbuscular mycorrhizal fungi: results from long-term field experiments. Ecol. Lett. 12, 452–461. Wortmann, C.S., Quincke, J.A., Drijber, R.A., Mamo, M., Franti, T., 2008. Soil microbial community change and recovery after one-time tillage of continuous no-till. Agron. J. 100, 1681–1686. Wright, S.F., Franke-Snyder, M., Morton, J.B., Upadhyaya, A., 1996. Time-course study and partial characterization of a protein on hyphae of arbuscular mycorrhizal fungi during active colonization of roots. Plant Soil 181, 193–203. Wright, S.F., Green, V.S., Cavigelli, M.A., 2007. Glomalin in aggregate size classes from three different farming systems. Soil Tillage Res. 94, 546–549.
397
Wright, A.L., Hons, F.M., 2005. Soil carbon and nitrogen storage in aggregates from different tillage and crop regimes. Soil Sci. Soc. Am. J. 69, 141–147. Wright, S.F., Starr, J.L., Paltineanu, I.C., 1999. Changes in aggregate stability and concentration of glomalin during tillage management transition. Soil Sci. Soc. Am. J. 63, 1825–1829. Wright, S.F., Upadhyaya, A., 1998. A survey of soils for aggregate stability and glomalin, a glycoprotein produced by hyphae of arbuscular mycorrhizal fungi. Plant Soil 198, 97–107. Yamashita, T., Flessa, H., John, B., Helfrich, M., Ludwig, B., 2006. Organic matter in density fractions of water-stable aggregates in silty soils: effect of land use. Soil Biol. Biochem. 38, 3222–3234. Young, I.M., Ritz, K., 2000. Tillage, habitat space and function of soil microbes. Soil Tillage Res. 53, 201–213. Zelles, L., Bai, Q.Y., Beck, T., Beese, F., 1992. Signature fatty acids in phospholipids and lipopolysaccharides as indicators of microbial biomass and community structure in agricultural soils. Soil Biol. Biochem. 24, 317–323. Zibilske, L.M., Bradford, J.M., 2007. Soil aggregation, aggregate carbon and nitrogen, and moisture retention induced by conservation tillage. Soil Sci. Soc. Am. J. 71, 793–802.