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Response of microbial communities to water stress in irrigated and drought-prone tallgrass prairie soils
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Soil Biology & Biochemistry 39 (2007) 2750–2757 www.elsevier.com/locate/soilbio
Response of microbial communities to water stress in irrigated and drought-prone tallgrass prairie soils Mark A. Williams Department of Plant and Soil Sciences, Mississippi State University, 470 Dorman Hall, MS 39759, USA Received 14 December 2006; received in revised form 10 May 2007; accepted 19 May 2007 Available online 26 June 2007
Abstract To better understand how water stress and availability affect the structure of microbial communities in soil, I measured the change in phospholipid fatty acids (PLFA) and the incorporation of 13C-labeled glucose into the PLFA following exposure to water stress. Overlaid on the laboratory water stress treatment, samples were collected from drought-prone and irrigated (11 years) tallgrass prairie soil (0–10 cm depth). In the laboratory, soils were either incubated at 250 kPa or dried steadily over a 3-d period to 45 MPa. On the fourth day, the dried samples were brought up to 250 kPa and then all samples received 250 mg of glucose-C (+4000 d13C-PDB) solution that brought them to 33 kPa matric water potential. Samples were then extracted for PLFA following 6 and 24 h of incubation (25 1C). Non-metric multidimensional scaling (NMS) techniques and multi-response permutation procedure (MRPP) showed that the largest effect on the mol% distribution of PLFA was related to the field scale water addition experiment. In response to irrigation, the PLFA 16:1o5, 18:1+, and 18:2o6,9 showed increases, and a15:0, a17:0, and cy19:0 showed decreases in their respective mol%. Effects related to the induction of laboratory water stress were predominantly associated with a decrease in the mol% distribution of the putative fungal biomarker (18:2o6,9) with little to no change in the mol% distribution of the bacterial biomarkers. Interestingly, the flow of C to the microbial community was not strongly related to any single PLFA, and differences were rather subtle, but multivariate MRPP detected change to the community structure related to the laboratory water stress treatment but not related to the 11 years of field irrigation. Our results suggest that both the total and the actively metabolizing bacterial community in soil were generally resistant to the effects of water stress brought by rewetting of dry soil. However, more research is needed to understand the nature of the fungal response to drying and rewetting in soil. r 2007 Elsevier Ltd. All rights reserved. Keywords:
13
C-PLFA compound-specific isotope analysis of microbial communities; Drying–rewetting
1. Introduction Water dynamics and stress exert a major influence on microbial physiology and function (Harris, 1981; Yancey et al., 1982; Kempf and Bremer, 1998), however, there is still considerable debate about how water stress affects soil microbial communities, their biomass, and their overall activity. One of the primary factors influencing microbial responses to soil water cycling is the situation of feast or famine that occurs in most ecosystems. The vast majority of ecosystems undergo short- and long-term droughts, which cause soil water contents to drastically decrease. Tel.: +1 662 325 2762; fax: +1 662 325 8742.
E-mail address: [email protected] 0038-0717/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2007.05.025
Eventually, water stress is alleviated either through rainfall or from irrigation (e.g. agro-ecosystems). While there is widespread agreement that drying and rewetting results in large immediate changes in nutrient cycles (Sorenson, 1974; Bottner, 1985; Appel, 1998), there is still considerable debate about the nature of abiotic and biotic responses that can mechanistically explain measured changes in soil processes. There is evidence for instance, that both microbial and non-microbial pools of C contribute to changing C and N pools and mineralization rates (Schimel et al., 1999; Denef et al., 2001; Steenworth et al., 2005; Cosentino et al., 2006). While both of these mechanisms are useful for explaining results from various studies, there have been relatively few definitive mechanistic explanations that can be used to explain the soil microbial response to
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drying and rewetting (Killham and Firestone, 1984; Kieft et al., 1987; Schimel et al., 1989; Scheu and Parkinson, 1994; Halverson et al., 2000; Fierer et al., 2002). It has been hypothesized that soils that naturally experience climatic conditions that promote high degrees of variability in water availability may be more adapted to water stress and may thus show a more limited response to drying and rewetting induced water stress. For instance, a drought-prone grassland soil responded much less to drying and rewetting than an oak-dominated soil that tend to have naturally more moderate variability in water potential (Fierer and Schimel, 2003). Other studies with soils taken from soil with naturally contrasting soil moisture regimes have shown, anecdotally, that this hypothesis may have widespread merit (van Gestel et al., 1993; Lundquist et al., 1999; Franzluebbers et al., 2000). It has also been hypothesized that active and growing members of microbial communities may be more susceptible to the effects of water stress than the whole and predominantly inactive or dormant microbial community. This hypothesis follows from the fact that soils are a lownutrient environment and that a large number of microorganisms are in a physiologically inactive or starvation state that should be expected to afford some protection from environmental disturbance (Chen and Alxexander, 1973). The one attempt at understanding the response of actively growing soil microorganisms was only capable of resolving rRNA structural differences in bacterial communities, which were small if non-existent to the effects of water stress (Griffiths et al., 2003). The objective of our study was to trace the movement of 13 C from glucose into the microbial PLFA to determine if the activity of the microbial community in continuously moist soil differed from that of soil exposed to drying and rewetting. Overlaid on this experiment, we also wanted to determine if there was altered response of the microbial community to water stress following 11 years of irrigation in a tallgrass prairie. By understanding the nature of the microbial community response, we can better explain the relative importance of drying and rewetting on community structure and turnover, and gain insight into the factors that contribute to flushes of C and nutrients following drying and rewetting. 2. Materials and methods 2.1. Site description The experiment was conducted in a native (annually burned in spring) upland tallgrass prairie located at the Konza Prairie Biological Station near Manhattan, KS, USA. Soils of the upland summit topographic position are dominated by mesic Typic Hapludolls (Benfield silty clay loam). Vegetation on the site was a mixture of C3 and C4 species, dominated by big bluestem (Andropogon gerardii) and Indian grass (Sorghastrum nutans (L.) Nash). Previously, it has been shown that average peak aboveground
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biomass (1993–2000) was approximately 575 and 455 g m2 in continuously moist and drought-prone transects, respectively, of which 35–50 g m2 was forbs (Knapp et al., 1998). Standing root biomass did not differ between treatments and was approximately 785 g m2 in the top 10 cm of soil (Williams, 2001). Many of the dominant grasses and forbs responded to irrigation through increased biomass production, but forbs showed the largest response (http:// climate.konza.ksu.edu/). Established in 1990 and 1993, the irrigation pipelines traversed a 70-m long by 30-m wide transect in the upland (280 m MSL) topographic position. Penman equations and meteorological data were used to calculate plant water demand, and water was added during the months of May/June through September (Penman, 1948; Knapp et al., 1998; Williams, 2001). During the other months of the year, precipitation exceeds evapotranspiration. In the driest year of 1991, an additional 470 mm of water was added in the irrigated treatments, whereas in the wettest year of 1993, only 80 mm of water was added. On average, 245 mm of water was added in each growing season, an amount equivalent to 60% of the average total rainfall during the 4-month period. The year of 2003 was a typically dry year with only 500 mm of rainfall recorded during the peak growing season months of May through September, resulting in an additional 245 mm of water added via irrigation (http:// climate.konza.ksu.edu). Four replicate irrigation plots (1.0 m2) were interspersed by four un-watered control plots. Details of the irrigation transects in the Konza Prairie LTER and their experimental design have been published previously (O’Lear and Blair, 1999; Todd et al., 1999; Williams and Rice, 2007). Soils that were irrigated were maintained at water potentials consistently above approximately 1500 kPa during the growing season, whereas soils that receive only natural rainfall inputs often drop well below 5000 kPa for extended periods of time (Williams, 2001). Twenty 2.2-cm dia by 10-cm deep soil cores were collected from each plot in late September 2003. After collecting, soils were immediately passed through a 4-mm mesh sieve, meticulously hand-cleaned of roots and organic debris, and stored at 4 1C for less than 2 weeks. Several natural rainfalls occurred during September, and as a result all soils had soil water contents between 32% and 34%. The relationship between soil water content and soil water (matric) potential was estimated using standard methods on freshly sieved soils that were repacked to the original bulk density (1.0 g cm3). The first method utilizes a porous ceramic plate that is used to make contact between a soils sample and a pressure differential up to 1500 kPa (Klute, 1986) in a closed system. The second method, known as the filter paper method, also measures water potential in a closed system. In this case, a Whatman #41 filter paper was incubated with a soil sample of known water content for 6 d. The amount of water adsorbed to the filter paper could be measured by an analytical balance and
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then used to estimate water potential as described by McInnes et al. (1994).
following equation: d13 CPLFA ¼
2.2. Pre-incubation and addition of
13
C-glucose to the soils
Field-moist soils (15 g dry weight) were weighed into 160-ml serum bottles and brought up to 250 kPa soil water content and incubated for 3 d (25 1C). One set of soils was kept moist at 0.25 MPa, and two sets were slowly and linearly dried over a 3-d period to 45 MPa. On the 4th day, the dried soils were brought back to 250 MPa over a 20-s period with a single addition of 5.5 g deionized water. A 0.5-ml solution of D-glucose (U-13C, d13CPDB ¼ +4000) containing 250 mg glucose C was immediately and evenly added to all of the soils resulting in a matric potential of 33 kPa. The continuously moist soil was extracted after 6 h, and the dried and rewetted soils were incubated for 6 and 24 h and then extracted for PLFA. Preliminary experiments suggested that the glucose was catabolized during a 6-h period. There were no significant changes in the mol% of total and glucosederived PLFA-C between sampling times, so results from the 6 h incubation and extraction are presented. 2.3. Extraction and analysis of soil PLFA Lipids were extracted according to the procedure of White and Ringelberg (1998) as modified by Butler et al. (2003). Briefly, portions of soil (15 g wet weight) were extracted overnight in a mixture of chloroform, methanol and 50 mM phosphate buffer (pH 7.1). Lipids were extracted the following day by centrifugation and filtration. Dried lipid extracts were re-dissolved in chloroform and separated into neutral, glyco- and phospholipids on solid phase silica columns (Supelco, Inc., Bellefonte, PA) with chloroform, acetone and methanol, respectively. The phospholipid fraction was recovered and saponified to obtain fatty acid methyl esters (FAME), and then analyzed by capillary GC–combustion–isotope ratio mass spectrometry (GC–C–IRMS). Chromatographic peaks were quantified using 13:0 and 19:0 methyl ester standards. Between 3.3 and 3.9 mmol of fatty acid C g1 soil were recovered from the samples; no significant differences were detected between the treatments or sampling times. The d13C values of individual PLFA were determined as described by Butler et al. (2003) with an Agilent 6890 gas chromatograph (Agilent Inc., Palo Alto, CA) equipped with a 30-m HP Innowax column (internal diameter, 0.25 mm; film thickness, 0.25 mm) connected to a Europa ORCHID on-line combustion interface in line with a Europa 20–20 mass spectrometer (Europa Scientific, Cheshire, England). During the methylation step, an additional C atom is added to the fatty acid molecule. This additional C atom, of known d13C value (44%), was corrected for the d13C values of the PLFA with the
½ðC PLFA þ 1Þ d13 CPFAME d13 CMeOH , C PFAME
(1)
where CPLFA and d13CPLFA refer to the number of C atoms and the d13C value, respectively, of the PLFA; CPFAME and d13CPFAME refer to the number of C atoms and the d13C value of the FAME after derivitization, and d13CMeOH refers to the d13C value of the methanol used for methylation. We calculated the proportion of residue derived PLFAC for each individual PLFA by using the following equation: F i ¼ Mc
ðdli dui Þ ; ðdgi dui Þ
i ¼ individual PLFA;
(2)
where Fi is the relative fraction of C in each PLFA composed of enriched 13C residue, Mc is the relative percentage of C in each PLFA to that of the total PLFA, dl represents the d13C of the PLFA-C derived from the 13C enriched residue, du represents the d13C of the PLFA-C derived from un-enriched residue, and dg represents the d13C of the labeled residue. The mol% or proportion (PFi) of glucose derived C for each PLFA to that of the total glucose derived PLFA-C for all fatty acids was then calculated for each fatty acid using the following equation: Fi PFi ¼ P 100. Fi
(3)
Standard nomenclature is used to describe PLFA. The number before the colon refers to the total number of C atoms; the number(s) following the colon refers to the number of double bonds and their location (after the ‘‘o’’) in the fatty acid molecule. Notations: ‘‘Me,’’ ‘‘cy,’’ ‘‘i,’’ and ‘‘a’’ refer to methyl group, cyclopropane groups, and isoand anteiso-branched fatty acids, respectively. Fifteen PLFA comprised 95% of the PLFA, and were each present in sufficient quantity to obtain accurate d13C values. Other indicator fatty acids such as hydroxy fatty acids and long chain fatty acids (XC20) were either below the limit of accurate detection, or present in amounts too small to get accurate d13C values. Two fatty acids (16:1o7 and 10Me16:0) merged (denoted as 16:1+) into one peak, as did 18:1o7 and 10Me18:0 (denoted as 18:1+). 2.4. Statistical analyses The ordination and multivariate analysis of the data utilized the PC-ORD version 4 software (MJM Software, Gleneden Beach, OR) and followed the recommendations of McCune and Grace (2002). The effects of field irrigation and laboratory drying and rewetting were analyzed using mol% of total and new C in the 15 dominant PLFA. Multivariate analysis was carried out using the multiresponse permutation procedure (MRPP). The MRPP is a non-parametric procedure for testing the hypothesis of no
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3.2. Water availability and stress effects on glucose C incorporation into the microbial community MRPP analysis showed that there was a significant effect of the laboratory but not the field level water addition experiment on the mol% distribution of PLFA-C derived from glucose. The two-dimensional NMS representation of this relationship can most easily be seen in Fig. 3. There were, however, no specific PLFA that showed significant differences between the different treatments (Fig. 4). In this regard, it is important to note the lower amount of variability attributed to Axis 2 than Axis 1. There was no interaction affect between the field and laboratory water treatments.
b
b
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** a b
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cy17:0
10me17:0
i17:0
a17:0
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Data presented in Fig. 1 show the mol% distribution of 15 analytically distinguishable PLFA extracted from soil. The distribution of PLFA-C between the laboratory water treatments were significantly different in only two specific cases, with drying and rewetting resulting in a mol% reduction in 10me17:0 and 18:2o6,9 (Fig. 1a vs 1b). The MRPP analysis of mol% PLFA-C indicated no difference in how soils that were continuously moist for 11 years or were drought prone responded to wetting and drying in the laboratory. However, compared to the drought-prone soil, the field treatment of 11 years of continuously high water availability resulted in mol% reductions of a15:0, a17:0 and cy19:0 and increases in 16:1o5, 18:1+ and 18:2o6,9. The extent of the effect of field irrigation compared to that of laboratory wetting and drying can also be seen in Fig. 2. Corroborating the univariate analysis noted in Fig. 1, the NMS and MRPP analysis show significant differences between the field water treatment with no effect of laboratory drying and rewetting on the multivariate spread of the data. There was no interaction effect between the field and laboratory water treatments.
b 10
a15:0
3.1. Microbial community structure in response to field and laboratory water stress
a
12
i15:0
3. Results
Continuously-moist Drought-prone
14
Distribution of C (mol%)
difference between two or more groups of entities. Nonmetric multidimensional scaling (NMS), also a nonparametric method, was used to provide graphical ordination of the mol% PLFA-C and mol% new PLFA-C data. Matrix dissimilarity was measured using the Sorenson distance measure. The preferred solution, based on the lowest stress and instability was two dimensional, resulting in a final stress of 12.4. Mol% for each individual and biomarker PLFA were analyzed using the univariate method of Proc Mixed (SAS Institute, 1996). The experiment was input as a strip plot design with the strip factors of field irrigation and laboratory drying–rewetting. LSD tests were used to determine where significant differences occurred (a ¼ 0.05).
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Fig. 1. The mol% distribution of total PLFA-C in soils maintained (a) moist, or (b) dried and rewetted in the laboratory. Continuously moist and drought-prone designations in the legend denote the treatments associated with the 11-year field-level irrigation experiment. Small case letters designate significant differences between the field water treatments and asterisks denote significant differences between the laboratory water stress treatments for that specific PLFA (n ¼ 4, Po0.05, LSD).
4. Discussion It was found that overall microbial community structure was altered more by the field level manipulation of water than by drying and rewetting induced water stress. I hypothesize that the change was related to the ongoing and cumulative differences that define the field level manipulation of water. These differences can be attributed to indirect effects, such as changing amounts of C input related to greater belowground plant biomass productivity in the continuously moist soils, in addition to any direct affects of water regime. Indeed, both C availability and water regime have been implicated as major determinants of soil microbial community structure in both laboratory and field-based experimental manipulations (Zhang and Zak, 1998; Frey et al., 1999; Wilkinson et al., 2002; Drenovsky et al., 2004).
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1.5
Continuously-moist, moist Drought-prone, moist Continuously-moist, dried and re-wet Drought-prone,dried and re-wet
Axis 2 (14%)
1.0
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10
-0.5 -1.0 -1.5 -1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
Axis 1 (82%) Fig. 2. Differences in the structure of the microbial community associated with the field and laboratory water experiments using a non-metric multidimensional scaling (NMS) analysis of the mol% PLFA-C. The designation noted first in the heading refers to the field manipulation of water, and the designations noted after the comma refer to the laboratory induction of drying and rewetting water stress. Percentages denote the amount of variability associated with each axis. Values of symbols represent the means of the treatment. The standard errors of the treatments, when larger than the size of the symbol, are noted along both axes (n ¼ 4).
Distribution of C (mol%)
5 0
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Axis 2 (19%)
cy19:0
18:1+
18:2ω6,9
18:0
18:1ω9
cy17:0
i17:0
a17:0
16:1+
16:1ω5
16:0
Fig. 4. The mol% distribution of PLFA-C derived from 13C-labeled glucose in soils maintained (a) moist, or (b) dried and rewetted in the laboratory. Continuously moist and drought-prone designations in the legend denote the treatments associated with the 11-year field-level irrigation experiment. Small case letters designate significant differences between the field water treatments and asterisks denote significant differences between the laboratory water stress treatments for that specific PLFA (n ¼ 4, Po0.05, LSD).
0.0
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0
Continuously-moist, moist Drought-prone, moist Continuously-moist, dry-rewet Drought-prone, dry-rewet
-1.0 -1.0
-0.5
0.0
0.5
1.0
Axis 1 (78%) Fig. 3. Differences in the structure of the glucose-metabolizing microbial community associated with the field and laboratory water experiments using a non-metric multidimensional scaling (NMS) analysis of the mol% PLFA-C. The designation noted first in the heading refers to the field manipulation of water, and the designations noted after the comma refers to the laboratory induction of drying and rewetting water stress. Percentages denote the amount of variability associated with each axis. Values of symbols and bars represent means and standard error, respectively (n ¼ 4).
With both types of water stress, whether through natural drought cycles common to tallgrass prairie or through the induction and alleviation of water deficit in the laboratory, there was 25% reduction in the mol% of the fungal PLFA marker (18:2o6,9) compared to situations where
water availability was kept more or less constant. Greater fungal to bacterial biomass ratios were previously reported to occur throughout the growing season as a result of 7 years enhancement of water availability in tallgrass prairie soil (Williams and Rice, 2007). While fungal microorganisms have traditionally been touted as highly resistant to water stress and are known to grow at relatively low water potentials (Harris, 1981; Schimel et al., 1989), these results suggest that perhaps there are groups in soil that may be particularly susceptible to soil water status and stress. Suffice it to say, the ability to grow at low water potential does not necessarily translate into the capacity to withstand the osmotic upshock that follows rewetting of dry soil. Fungal biomass reductions related to drying and rewetting stress have been noted by other researchers (Denef et al., 2001), suggesting that the generalization that fungi are
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relatively resistant to water stress is in need of further verification. In light of the fact that the microbial biomass in the prairie soils are dominated by fungi (Bailey et al., 2002; Williams and Rice, 2007), the reduction in the mol% of the fungal biomarker to water stress, which could suggest fungal turnover resulting from cell lysis, could also be representative of a substantial change in fungal community structure. This would be the case if certain types or groups of fungi were sensitive to osmotic upshock. Unfortunately, PLFA analysis is not capable of resolving these possible differences. In contrast, the bulk of the PLFA, not including the 18:2o6,9 and 18:1o9, are probably most representative of bacterial communities (Bossio and Scow, 1998; Bailey et al., 2002). The lack of significant change in mol% distribution in these PLFA is in agreement with recent reports that bacterial communities in soils appear to be relatively resilient and/or adaptable to the effects of drying and rewetting (Wilkinson and Anderson, 2001; Fierer et al., 2002; Griffiths et al., 2003). Other studies of soil prokaryotic communities suggest that some soil bacterial communities can be sensitive to drying and rewetting (Fierer et al., 2002; Pesaro et al., 2004). However, with these latter studies it is difficult to garner a sense of the magnitude of the community change compared to that of other environmental drivers. In the context of the response of the fungal PLFA (18:2o6,9) to rewetting of dry soil, it was interesting to note that, regardless of treatment, only a small fraction of new C (mol% 1) flowed into this PLFA. This result would seem to suggest that only a small subset of the fungal community responded to the glucose addition. If only a small component of the community was actively growing on the glucose, this limits extrapolation as to how the broader fungal community might respond to water stress. We cannot rule out the possibility, furthermore, that this low response by the fungal community may be analogous to the negative influence that tillage may have on fungal communities (Wardle, 1995). As such, the fungal biomass response to drying and rewetting may have been partially precipitated by the disturbance initiated by the sampling and sieving of the soil, and may have inadvertently increased their susceptibility to water stress and lowered the response of the fungi to glucose addition. While we tried to strike a balance between preincubation of the soils before initiation of the experiment to help offset disturbance effects, we also did not want to over-incubate the soils and risk changing the conditions that might then override or mask the effects manifested in the field experiment. It is also important to note that the degree of drying that we inflicted on the soil and its community members was not a typical yearly drying scenario, but more an extreme that would occur in the driest years, perhaps two to three times per decade (Garcia, 1992; Williams, 2001). Hence, a more typical water deficit in soil may not have the same detrimental effect on the
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fungal biomass. More research using several different levels of water stress and using undisturbed soil will help resolve these questions. By utilizing high-resolution isotope techniques and focusing on the most active, growing, and presumably the most sensitive subset of the community we expected to see changes in the way that the metabolically active community members utilized glucose, a molecule that is constitutively utilized by a widespread set of microorganisms. In this way, for example, we expected to see that some biomarkers, such as those of less dilution stress tolerant gram-negative microorganisms (16:1o7, 18:1o7, cy17:0, cy19:0) to show marked reductions in the amount of glucose-C, while gram-positive types (i15:0, a15:0 i16:0, i17:0) which have been shown to be more water stress tolerant would show definitive increases in glucose-derived C (Harris, 1981; Halverson et al., 2000). However, even with the significant change in the structure of the actively growing microbial community in response to drying and rewetting, there were no specific changes in PLFA, and the structural alterations seemed small and unremarkable compared to the overall similarities in the distribution of glucose-C within the community. In contrast to communities derived from soils in more humid and moist regions, it has been previously hypothesized that communities derived from arid and drymesic type systems, such as the tallgrass prairie, may be naturally resistant and adaptable to drying–rewetting induced water stress (van Gestel et al., 1993; Fierer et al., 2002; Pesaro et al., 2004), a view that is generically supported by our work. The small but structurally similar change in the actively growing community in response to drying and rewetting stress by both field water availability treatments makes sense in light of the soil conditions at sampling. When sampled in late September, the water contents and presumably other environmental factors such as temperature were similar between the continuously moist and drought-prone soils. While it was shown that the structure of the total microbial community with contrasting water regimes are distinctive from each other, the response of the actively metabolizing community may be more closely related to the immediate environmental conditions rather than historical treatment effects. Indeed, previous research that studied the functional response of the cultivable community bears this possibility out (Griffiths et al., 2003; Williams and Rice, 2007). Presuming that the two active microbial communities were similar, it is then no surprise that the drought-prone and continuously moist field soils responded similarly to drying and rewetting induced water stress under laboratory conditions. Based on observations for glucose-responsive community members, and the overall dynamic nature of soil microbial communities related to seasonal influences, the response of the active community members needs further study. Indeed, even the small non-specific change that we
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noted in the flow of C to PLFA may be more indicative of physiological rather than structural community change. However, if it turns out to be a broad truism that microbial community structure does not change or changes very little in response to drying and rewetting induced water stress, then other mechanisms are needed that can account for flushes of C and N that typically follow the wetting of dry soil. One popular hypothesis suggests that microorganisms in soil are responding and adapting to the drying phase of water stress through the accumulation of organic cytoplasmic solutes (alcohols, amino acids). Upon rewetting, these solutes are expelled from the biomass and redistributed into the extracellular soil matrix where they are quickly mineralized (Kieft et al., 1987; Halverson et al., 2000; Fierer and Schimel, 2003). This hypothesis has merit in that a microbial response of this type has been widely measured in cultured systems (Tschicholz and Truper, 1990; Schleyer et al., 1993; Halverson et al., 2000). It also has the advantage of helping to explain both the increase in carbon dioxide and N production rates that typically occur immediately following the rewetting of dry soil. Lastly, it also helps to explain the resilience of the microbial community structure by invoking a known physiological adaptation to sudden and large water potential changes that occur in most soils. This hypothesis does not rule out the possible contributions of non-microbial sources of mineralizable C such as that released through physical slaking or the breakdown of aggregates that have been shown to follow drying and rewetting (Degens and Sparling, 1995; Denef et al., 2001; Cosentino et al., 2006). Indeed, there is still evidence that both microbial and nonmicrobial sources play an important role in contributing to the nutrient flushes released when rewetting of dried soil (Mikha et al., 2005; Wu and Brookes, 2005). The results of this study have interesting implications regarding the mechanisms of community response to drying and rewetting. In the light of other research, and if the broader PLFA results can be said to be representative of the general community response, soil microbial communities as a whole appear to be rather well adapted to water stress. By exclusion this would suggest that process changes (e.g., C and N flushes) that can be attributed to soil biology might be best explained by physiological and functional changes rather than structural changes in communities. However, more research is needed to understand the nature of the microbial, and especially the fungal response to drying and rewetting in soil.
Acknowledgments I appreciate the field and laboratory support provided by Jami Schaffner and Amy Thompson. This research was funded by a competitive grant from the Soil Processes Division within USDA-NRI. Special thanks is extended to the Konza Prairie Biological Station for providing access to their long-term irrigation experiment.
References Appel, T., 1998. Non-biomass soil organic N—the substrate for N mineralization flushes following soil drying-rewetting and for organic N rendered CaCl2-extractable upon soil drying. Soil Biology & Biochemistry 30, 1445–1456. Bailey, V.L., Peacock, Smith, J.L., Bolton Jr., H., 2002. Relationships between soil microbial biomass determined by chloroform fumigation– extraction, substrate-induced respiration, and phospholipid fatty acid analysis. Soil Biology & Biochemistry 34, 1385–1389. Bossio, D.A., Scow, K.M., 1998. Impacts of carbon and flooding on soil microbial communities: phospholipid fatty acid profiles and substrate utilization patterns. Microbial Ecology 35, 265–278. Bottner, P., 1985. Response of microbial biomass to alternate moist and dry conditions in a soil incubated with carbon-14-and nitrogen-15-labeled plant material. Soil Biology & Biochemistry 17, 329–337. Butler, J.L., Williams, M.A., Bottomley, P.J., Myrold, D.D., 2003. Microbial community dynamics associated with rhizosphere C flow. Applied and Environmental Microbiology 69, 6793–6800. Chen, M., Alxexander, M., 1973. Survival of soil bacteria during prolonged dessication. Soil Biology & Biochemistry 5, 213–221. Cosentino, D., Chenu, C., Le Bissonnais, Y., 2006. Aggregate stability and microbial community dynamics under drying-wetting cycles in a silt loam soil. Soil Biology & Biochemistry 38, 2053–2062. Degens, B.P., Sparling, G.P., 1995. Repeated wet-dry cycles do not accelerate the mineralization of organic C involved in the macroaggregation of a sandy loam soil. Plant and Soil 175, 197–203. Denef, K., Six, J., Paustian, K., Merchkx, R., 2001. Importance of macroaggregate dynamics in controlling soil carbon stabilization: short-term effects of physical disturbance induced by dry–wet cycles. Soil Biology & Biochemistry 33, 2145–2153. Drenovsky, R.E., Vo, D., Graham, K.J., Scow, K.M., 2004. Soil water content and organic carbon availability are major determinants of soil microbial community composition. Microbial Ecology 48, 424–430. Fierer, N., Schimel, J.P., 2003. A proposed mechanism for the pulse in carbon dioxide production commonly observed following the rapid rewetting of a dry soil. Soil Science Society of America Journal 67, 798–805. Fierer, N., Schimel, J.P., Holden, P.A., 2002. Influence of drying–rewetting frequency on soil bacterial community structure. Microbial Ecology 45, 63–71. Franzluebbers, A.J., Haney, R.L., Honeycutt, C.W., Schomberg, H.H., Hons, F.M., 2000. Flush of carbon dioxide following rewetting of dried soil related to active organic pools. Soil Science Society of America Journal 64, 613–623. 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 Biology & Biochemistry 31, 573–585. Garcia, F., 1992. Carbon and nitrogen dynamics and microbial ecology in tallgrass prairie. Ph.D. Dissertation, Kansas State University, Manhattan, KS, 194pp. Griffiths, R.I., Whiteley, A.S., O’Donnell, A.G., Bailey, M.J., 2003. Physiological and community responses of established grassland bacterial populations to water stress. Applied Environmental Microbiology 69, 6961–6968. Halverson, L.J., Jones, T.M., Firestone, M.K., 2000. Release of intracellular solutes by four soil bacteria exposed to dilution stress. Soil Science Society of America Journal 64, 1630–1637. Harris, R.F., 1981. Effect of water potential on microbial growth and activity in soils. In: Parr, J.F., Gardner, W.R., Elliott L.F. (Eds.), Water Potential Relations in Soil Microbiology. Soil Science Society of America Journal, Madison, WI, pp. 23–96. Kempf, B., Bremer, E., 1998. Uptake and synthesis of compatible solutes as microbial stress responses to high-osmolality environments. Archives of Microbiology 170, 319–330.
ARTICLE IN PRESS M.A. Williams / Soil Biology & Biochemistry 39 (2007) 2750–2757 Kieft, T.L., Soroker, E., Firestone, M., 1987. Microbial biomass response to a rapid increase in water potential when dry soil is wetted. Soil Biology & Biochemistry 19, 119–126. Killham, K., Firestone, M.K., 1984. Salt stress control of intracellular solutes in streptomycetes indigenous to saline soils. Applied and Environmental Microbiology 47, 301–306. Klute, A., 1986. Water Retention. In: Klute, A. (Ed.), Methods of soil analysis, physical and mineralogical methods. Soil Science Society of America Journal, Madison, WI, pp. 635–642. Knapp, A., Briggs, J., Blair, J., Turner, C., 1998. Patterns and controls of aboveground net primary production in tallgrass prairie. In: Knapp, A.K., Hartnett, D.C., Collins, S.L. (Eds.), Grassland Dynamics, Long-term Ecological Research in Tallgrass prairie. Oxford University Press, New York, pp. 193–221. Lundquist, E.J., Scow, K.M., Jackson, L.E., Uesugi, S.L., Johnson, C.R., 1999. Rapid response of soil microbial communities from conventional, low input, and organic farming systems to a wet/dry cycle. Soil Biology & Biochemistry 31, 1661–1675. McCune, B., Grace, J.B., 2002. Analysis of Ecological Communities. MjM Software Design, Gleneden Beach, OR. McInnes, K.J., Weaver, R.W., Savage, M.J., 1994. Soil water potential. In: Weaver, R.W. (Ed.), Methods of soil analysis. Part 2. Microbiological and biochemical properties. Soil Science Society of America, Madison, WI, pp. 53–58. Mikha, M.M., Rice, C.W., Milliken, G.A., 2005. Carbon and nitrogen mineralization as affected by drying and wetting cycles. Soil Biology & Biochemistry 37, 339–347. O’Lear, H.A., Blair, J.M., 1999. Responses of soil microarthropods to changes in soil water availability in tallgrass prairie. Biology and Fertility of Soils 29, 207–217. Penman, H.L., 1948. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London A 194, 120–145. Pesaro, M., Gilles, N., Zeyer, J., Widmer, F., 2004. Impact of soil drying–rewetting stress on microbial communities and activities and on degradation of two crop protection products. Applied and Environmental Microbiology 70, 2577–2587. SAS Institute, 1996. SAS system for Mixed Models. SAS Inst., Cary, NC. Scheu, S., Parkinson, D., 1994. Changes in bacterial and fungal biomass C, bacterial and fungal biovolume and ergosterol content after drying, remoistening and incubation of different layers of cold temperate forest soils. Soil Biology & Biochemistry 26, 1515–1525. Schimel, J.P., Scott, W.J., Killham, K., 1989. Changes in cytoplasmic carbon and nitrogen pools in a soil bacterium and a fungus in response to salt stress. Applied Environmental Microbiology 55, 1635–1637. Schimel, J.P., Gulledge, J.M., Clein-Curley, J.S., Lindstrom, J.E., Braddock, J.F., 1999. Moisture effects on microbial activity and community structure in decomposing birch litter in the Alaskan taiga. Soil Biology & Biochemistry 31, 831–838. Schleyer, M., Schmid, R., Bakker, E.P., 1993. Transient, specific and extremely rapid release of osmolytes from growing cells of Escherichia
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coli K-12 exposed to hypoosmotic shock. Archives of Microbiology 160, 424–431. Sorenson, L.H., 1974. Rate of decomposition of organic matter in soil as influenced by repeated air drying–rewetting and repeated additions of organic material. Soil Biology & Biochemistry 6, 287–292. Steenworth, K.L., Jacson, L.E., Calderon, F.J., Scow, K.M., Rolston, D.E., 2005. Response of microbial community composition and activity in agricultural and grassland soils after a simulated rainfall. Soil Biology & Biochemistry 37, 2249–2262. Todd, T.C., Blair, J.M., Milliken, G.A., 1999. Effects of altered soil water availability on a tallgrass prairie nematode community. Applied Soil Ecology 13, 45–55. Tschicholz, I., Truper, H.G., 1990. Fate of compatible solutes during dilution stress in Ectothiorhodospira halochloris. FEMS Microbiology Ecology 73, 181–186. van Gestel, M., Merckx, R., Vlassak, K., 1993. Soil drying and rewetting and the turnover of 14C-labelled plant residues: first order decay rates of biomass and non biomass 14C. Soil Biology & Biochemistry 25, 125–134. Wardle, D.A., 1995. Impacts of disturbance on detitus food webs in agroecosystems of contrasting tillage and weed management practices. Advances in Ecological Research 26, 105–185. White, D.C., Ringelberg, D.B., 1998. Signature lipid biomarker analysis. In: Burlage, R.S., Atlas, D., Stahl, D., Geesey, G., Saylor, G. (Eds.), Techniques in Microbial Ecology. Oxford University Press, New York, pp. 255–272. Wilkinson, S.C., Anderson, J.M., 2001. Spatial patterns of soil microbial communities in a Norway spruce (Picea abies) plantation. Microbial Ecology 42, 248–255. Wilkinson, S.C., Anderson, J.M., Scardelis, S.P., Tisiafouli, M., Taylor, A., Wolters, V., 2002. PLFA profiles of microbial communities in decomposing conifer litters subject to moisture stress. Soil Biology & Biochemistry 34, 189–200. Williams, M.A., 2001. Influence of water on the carbon and nitrogen dynamics of annually-burned tallgrass prairie. Ph.D. Dissertation, Kansas State University, Manhattan, 206pp. Williams, M.A., Rice, C.W., 2007. Seven years of enhanced water availability influences the physiological, structural, and functional attributes of a soil microbial community. Applied Soil Ecology 35, 535–545. Wu, J., Brookes, P.C., 2005. The proportional mineralization of microbial biomass and organic matter caused by air-drying and rewetting of a grassland soil. Soil Biology & Biochemistry 37, 507–515. Yancey, P.H., Clark, M.E., Hand, S.C., Bowlus, R.D., Somero, G.N., 1982. Living with water stress: evolution of osmolyte systems. Science 217, 1214–1222. Zhang, Q., Zak, J.C., 1998. Potential physiological activities of fungi and bacteria in relation to plant litter decomposition along a gap size gradient in a natural subtropical forest. Microbial Ecology 35, 172–179.
Soil Biology & Biochemistry 39 (2007) 2750–2757 www.elsevier.com/locate/soilbio
Response of microbial communities to water stress in irrigated and drought-prone tallgrass prairie soils Mark A. Williams Department of Plant and Soil Sciences, Mississippi State University, 470 Dorman Hall, MS 39759, USA Received 14 December 2006; received in revised form 10 May 2007; accepted 19 May 2007 Available online 26 June 2007
Abstract To better understand how water stress and availability affect the structure of microbial communities in soil, I measured the change in phospholipid fatty acids (PLFA) and the incorporation of 13C-labeled glucose into the PLFA following exposure to water stress. Overlaid on the laboratory water stress treatment, samples were collected from drought-prone and irrigated (11 years) tallgrass prairie soil (0–10 cm depth). In the laboratory, soils were either incubated at 250 kPa or dried steadily over a 3-d period to 45 MPa. On the fourth day, the dried samples were brought up to 250 kPa and then all samples received 250 mg of glucose-C (+4000 d13C-PDB) solution that brought them to 33 kPa matric water potential. Samples were then extracted for PLFA following 6 and 24 h of incubation (25 1C). Non-metric multidimensional scaling (NMS) techniques and multi-response permutation procedure (MRPP) showed that the largest effect on the mol% distribution of PLFA was related to the field scale water addition experiment. In response to irrigation, the PLFA 16:1o5, 18:1+, and 18:2o6,9 showed increases, and a15:0, a17:0, and cy19:0 showed decreases in their respective mol%. Effects related to the induction of laboratory water stress were predominantly associated with a decrease in the mol% distribution of the putative fungal biomarker (18:2o6,9) with little to no change in the mol% distribution of the bacterial biomarkers. Interestingly, the flow of C to the microbial community was not strongly related to any single PLFA, and differences were rather subtle, but multivariate MRPP detected change to the community structure related to the laboratory water stress treatment but not related to the 11 years of field irrigation. Our results suggest that both the total and the actively metabolizing bacterial community in soil were generally resistant to the effects of water stress brought by rewetting of dry soil. However, more research is needed to understand the nature of the fungal response to drying and rewetting in soil. r 2007 Elsevier Ltd. All rights reserved. Keywords:
13
C-PLFA compound-specific isotope analysis of microbial communities; Drying–rewetting
1. Introduction Water dynamics and stress exert a major influence on microbial physiology and function (Harris, 1981; Yancey et al., 1982; Kempf and Bremer, 1998), however, there is still considerable debate about how water stress affects soil microbial communities, their biomass, and their overall activity. One of the primary factors influencing microbial responses to soil water cycling is the situation of feast or famine that occurs in most ecosystems. The vast majority of ecosystems undergo short- and long-term droughts, which cause soil water contents to drastically decrease. Tel.: +1 662 325 2762; fax: +1 662 325 8742.
E-mail address: [email protected] 0038-0717/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2007.05.025
Eventually, water stress is alleviated either through rainfall or from irrigation (e.g. agro-ecosystems). While there is widespread agreement that drying and rewetting results in large immediate changes in nutrient cycles (Sorenson, 1974; Bottner, 1985; Appel, 1998), there is still considerable debate about the nature of abiotic and biotic responses that can mechanistically explain measured changes in soil processes. There is evidence for instance, that both microbial and non-microbial pools of C contribute to changing C and N pools and mineralization rates (Schimel et al., 1999; Denef et al., 2001; Steenworth et al., 2005; Cosentino et al., 2006). While both of these mechanisms are useful for explaining results from various studies, there have been relatively few definitive mechanistic explanations that can be used to explain the soil microbial response to
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drying and rewetting (Killham and Firestone, 1984; Kieft et al., 1987; Schimel et al., 1989; Scheu and Parkinson, 1994; Halverson et al., 2000; Fierer et al., 2002). It has been hypothesized that soils that naturally experience climatic conditions that promote high degrees of variability in water availability may be more adapted to water stress and may thus show a more limited response to drying and rewetting induced water stress. For instance, a drought-prone grassland soil responded much less to drying and rewetting than an oak-dominated soil that tend to have naturally more moderate variability in water potential (Fierer and Schimel, 2003). Other studies with soils taken from soil with naturally contrasting soil moisture regimes have shown, anecdotally, that this hypothesis may have widespread merit (van Gestel et al., 1993; Lundquist et al., 1999; Franzluebbers et al., 2000). It has also been hypothesized that active and growing members of microbial communities may be more susceptible to the effects of water stress than the whole and predominantly inactive or dormant microbial community. This hypothesis follows from the fact that soils are a lownutrient environment and that a large number of microorganisms are in a physiologically inactive or starvation state that should be expected to afford some protection from environmental disturbance (Chen and Alxexander, 1973). The one attempt at understanding the response of actively growing soil microorganisms was only capable of resolving rRNA structural differences in bacterial communities, which were small if non-existent to the effects of water stress (Griffiths et al., 2003). The objective of our study was to trace the movement of 13 C from glucose into the microbial PLFA to determine if the activity of the microbial community in continuously moist soil differed from that of soil exposed to drying and rewetting. Overlaid on this experiment, we also wanted to determine if there was altered response of the microbial community to water stress following 11 years of irrigation in a tallgrass prairie. By understanding the nature of the microbial community response, we can better explain the relative importance of drying and rewetting on community structure and turnover, and gain insight into the factors that contribute to flushes of C and nutrients following drying and rewetting. 2. Materials and methods 2.1. Site description The experiment was conducted in a native (annually burned in spring) upland tallgrass prairie located at the Konza Prairie Biological Station near Manhattan, KS, USA. Soils of the upland summit topographic position are dominated by mesic Typic Hapludolls (Benfield silty clay loam). Vegetation on the site was a mixture of C3 and C4 species, dominated by big bluestem (Andropogon gerardii) and Indian grass (Sorghastrum nutans (L.) Nash). Previously, it has been shown that average peak aboveground
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biomass (1993–2000) was approximately 575 and 455 g m2 in continuously moist and drought-prone transects, respectively, of which 35–50 g m2 was forbs (Knapp et al., 1998). Standing root biomass did not differ between treatments and was approximately 785 g m2 in the top 10 cm of soil (Williams, 2001). Many of the dominant grasses and forbs responded to irrigation through increased biomass production, but forbs showed the largest response (http:// climate.konza.ksu.edu/). Established in 1990 and 1993, the irrigation pipelines traversed a 70-m long by 30-m wide transect in the upland (280 m MSL) topographic position. Penman equations and meteorological data were used to calculate plant water demand, and water was added during the months of May/June through September (Penman, 1948; Knapp et al., 1998; Williams, 2001). During the other months of the year, precipitation exceeds evapotranspiration. In the driest year of 1991, an additional 470 mm of water was added in the irrigated treatments, whereas in the wettest year of 1993, only 80 mm of water was added. On average, 245 mm of water was added in each growing season, an amount equivalent to 60% of the average total rainfall during the 4-month period. The year of 2003 was a typically dry year with only 500 mm of rainfall recorded during the peak growing season months of May through September, resulting in an additional 245 mm of water added via irrigation (http:// climate.konza.ksu.edu). Four replicate irrigation plots (1.0 m2) were interspersed by four un-watered control plots. Details of the irrigation transects in the Konza Prairie LTER and their experimental design have been published previously (O’Lear and Blair, 1999; Todd et al., 1999; Williams and Rice, 2007). Soils that were irrigated were maintained at water potentials consistently above approximately 1500 kPa during the growing season, whereas soils that receive only natural rainfall inputs often drop well below 5000 kPa for extended periods of time (Williams, 2001). Twenty 2.2-cm dia by 10-cm deep soil cores were collected from each plot in late September 2003. After collecting, soils were immediately passed through a 4-mm mesh sieve, meticulously hand-cleaned of roots and organic debris, and stored at 4 1C for less than 2 weeks. Several natural rainfalls occurred during September, and as a result all soils had soil water contents between 32% and 34%. The relationship between soil water content and soil water (matric) potential was estimated using standard methods on freshly sieved soils that were repacked to the original bulk density (1.0 g cm3). The first method utilizes a porous ceramic plate that is used to make contact between a soils sample and a pressure differential up to 1500 kPa (Klute, 1986) in a closed system. The second method, known as the filter paper method, also measures water potential in a closed system. In this case, a Whatman #41 filter paper was incubated with a soil sample of known water content for 6 d. The amount of water adsorbed to the filter paper could be measured by an analytical balance and
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then used to estimate water potential as described by McInnes et al. (1994).
following equation: d13 CPLFA ¼
2.2. Pre-incubation and addition of
13
C-glucose to the soils
Field-moist soils (15 g dry weight) were weighed into 160-ml serum bottles and brought up to 250 kPa soil water content and incubated for 3 d (25 1C). One set of soils was kept moist at 0.25 MPa, and two sets were slowly and linearly dried over a 3-d period to 45 MPa. On the 4th day, the dried soils were brought back to 250 MPa over a 20-s period with a single addition of 5.5 g deionized water. A 0.5-ml solution of D-glucose (U-13C, d13CPDB ¼ +4000) containing 250 mg glucose C was immediately and evenly added to all of the soils resulting in a matric potential of 33 kPa. The continuously moist soil was extracted after 6 h, and the dried and rewetted soils were incubated for 6 and 24 h and then extracted for PLFA. Preliminary experiments suggested that the glucose was catabolized during a 6-h period. There were no significant changes in the mol% of total and glucosederived PLFA-C between sampling times, so results from the 6 h incubation and extraction are presented. 2.3. Extraction and analysis of soil PLFA Lipids were extracted according to the procedure of White and Ringelberg (1998) as modified by Butler et al. (2003). Briefly, portions of soil (15 g wet weight) were extracted overnight in a mixture of chloroform, methanol and 50 mM phosphate buffer (pH 7.1). Lipids were extracted the following day by centrifugation and filtration. Dried lipid extracts were re-dissolved in chloroform and separated into neutral, glyco- and phospholipids on solid phase silica columns (Supelco, Inc., Bellefonte, PA) with chloroform, acetone and methanol, respectively. The phospholipid fraction was recovered and saponified to obtain fatty acid methyl esters (FAME), and then analyzed by capillary GC–combustion–isotope ratio mass spectrometry (GC–C–IRMS). Chromatographic peaks were quantified using 13:0 and 19:0 methyl ester standards. Between 3.3 and 3.9 mmol of fatty acid C g1 soil were recovered from the samples; no significant differences were detected between the treatments or sampling times. The d13C values of individual PLFA were determined as described by Butler et al. (2003) with an Agilent 6890 gas chromatograph (Agilent Inc., Palo Alto, CA) equipped with a 30-m HP Innowax column (internal diameter, 0.25 mm; film thickness, 0.25 mm) connected to a Europa ORCHID on-line combustion interface in line with a Europa 20–20 mass spectrometer (Europa Scientific, Cheshire, England). During the methylation step, an additional C atom is added to the fatty acid molecule. This additional C atom, of known d13C value (44%), was corrected for the d13C values of the PLFA with the
½ðC PLFA þ 1Þ d13 CPFAME d13 CMeOH , C PFAME
(1)
where CPLFA and d13CPLFA refer to the number of C atoms and the d13C value, respectively, of the PLFA; CPFAME and d13CPFAME refer to the number of C atoms and the d13C value of the FAME after derivitization, and d13CMeOH refers to the d13C value of the methanol used for methylation. We calculated the proportion of residue derived PLFAC for each individual PLFA by using the following equation: F i ¼ Mc
ðdli dui Þ ; ðdgi dui Þ
i ¼ individual PLFA;
(2)
where Fi is the relative fraction of C in each PLFA composed of enriched 13C residue, Mc is the relative percentage of C in each PLFA to that of the total PLFA, dl represents the d13C of the PLFA-C derived from the 13C enriched residue, du represents the d13C of the PLFA-C derived from un-enriched residue, and dg represents the d13C of the labeled residue. The mol% or proportion (PFi) of glucose derived C for each PLFA to that of the total glucose derived PLFA-C for all fatty acids was then calculated for each fatty acid using the following equation: Fi PFi ¼ P 100. Fi
(3)
Standard nomenclature is used to describe PLFA. The number before the colon refers to the total number of C atoms; the number(s) following the colon refers to the number of double bonds and their location (after the ‘‘o’’) in the fatty acid molecule. Notations: ‘‘Me,’’ ‘‘cy,’’ ‘‘i,’’ and ‘‘a’’ refer to methyl group, cyclopropane groups, and isoand anteiso-branched fatty acids, respectively. Fifteen PLFA comprised 95% of the PLFA, and were each present in sufficient quantity to obtain accurate d13C values. Other indicator fatty acids such as hydroxy fatty acids and long chain fatty acids (XC20) were either below the limit of accurate detection, or present in amounts too small to get accurate d13C values. Two fatty acids (16:1o7 and 10Me16:0) merged (denoted as 16:1+) into one peak, as did 18:1o7 and 10Me18:0 (denoted as 18:1+). 2.4. Statistical analyses The ordination and multivariate analysis of the data utilized the PC-ORD version 4 software (MJM Software, Gleneden Beach, OR) and followed the recommendations of McCune and Grace (2002). The effects of field irrigation and laboratory drying and rewetting were analyzed using mol% of total and new C in the 15 dominant PLFA. Multivariate analysis was carried out using the multiresponse permutation procedure (MRPP). The MRPP is a non-parametric procedure for testing the hypothesis of no
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3.2. Water availability and stress effects on glucose C incorporation into the microbial community MRPP analysis showed that there was a significant effect of the laboratory but not the field level water addition experiment on the mol% distribution of PLFA-C derived from glucose. The two-dimensional NMS representation of this relationship can most easily be seen in Fig. 3. There were, however, no specific PLFA that showed significant differences between the different treatments (Fig. 4). In this regard, it is important to note the lower amount of variability attributed to Axis 2 than Axis 1. There was no interaction affect between the field and laboratory water treatments.
b
b
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a
8
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** a b
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18:0
cy17:0
10me17:0
i17:0
a17:0
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i16:0
Data presented in Fig. 1 show the mol% distribution of 15 analytically distinguishable PLFA extracted from soil. The distribution of PLFA-C between the laboratory water treatments were significantly different in only two specific cases, with drying and rewetting resulting in a mol% reduction in 10me17:0 and 18:2o6,9 (Fig. 1a vs 1b). The MRPP analysis of mol% PLFA-C indicated no difference in how soils that were continuously moist for 11 years or were drought prone responded to wetting and drying in the laboratory. However, compared to the drought-prone soil, the field treatment of 11 years of continuously high water availability resulted in mol% reductions of a15:0, a17:0 and cy19:0 and increases in 16:1o5, 18:1+ and 18:2o6,9. The extent of the effect of field irrigation compared to that of laboratory wetting and drying can also be seen in Fig. 2. Corroborating the univariate analysis noted in Fig. 1, the NMS and MRPP analysis show significant differences between the field water treatment with no effect of laboratory drying and rewetting on the multivariate spread of the data. There was no interaction effect between the field and laboratory water treatments.
b 10
a15:0
3.1. Microbial community structure in response to field and laboratory water stress
a
12
i15:0
3. Results
Continuously-moist Drought-prone
14
Distribution of C (mol%)
difference between two or more groups of entities. Nonmetric multidimensional scaling (NMS), also a nonparametric method, was used to provide graphical ordination of the mol% PLFA-C and mol% new PLFA-C data. Matrix dissimilarity was measured using the Sorenson distance measure. The preferred solution, based on the lowest stress and instability was two dimensional, resulting in a final stress of 12.4. Mol% for each individual and biomarker PLFA were analyzed using the univariate method of Proc Mixed (SAS Institute, 1996). The experiment was input as a strip plot design with the strip factors of field irrigation and laboratory drying–rewetting. LSD tests were used to determine where significant differences occurred (a ¼ 0.05).
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Fig. 1. The mol% distribution of total PLFA-C in soils maintained (a) moist, or (b) dried and rewetted in the laboratory. Continuously moist and drought-prone designations in the legend denote the treatments associated with the 11-year field-level irrigation experiment. Small case letters designate significant differences between the field water treatments and asterisks denote significant differences between the laboratory water stress treatments for that specific PLFA (n ¼ 4, Po0.05, LSD).
4. Discussion It was found that overall microbial community structure was altered more by the field level manipulation of water than by drying and rewetting induced water stress. I hypothesize that the change was related to the ongoing and cumulative differences that define the field level manipulation of water. These differences can be attributed to indirect effects, such as changing amounts of C input related to greater belowground plant biomass productivity in the continuously moist soils, in addition to any direct affects of water regime. Indeed, both C availability and water regime have been implicated as major determinants of soil microbial community structure in both laboratory and field-based experimental manipulations (Zhang and Zak, 1998; Frey et al., 1999; Wilkinson et al., 2002; Drenovsky et al., 2004).
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1.5
Continuously-moist, moist Drought-prone, moist Continuously-moist, dried and re-wet Drought-prone,dried and re-wet
Axis 2 (14%)
1.0
Continuously-moist 20
0.5
Drought-prone
15
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10
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1.0
1.5
Axis 1 (82%) Fig. 2. Differences in the structure of the microbial community associated with the field and laboratory water experiments using a non-metric multidimensional scaling (NMS) analysis of the mol% PLFA-C. The designation noted first in the heading refers to the field manipulation of water, and the designations noted after the comma refer to the laboratory induction of drying and rewetting water stress. Percentages denote the amount of variability associated with each axis. Values of symbols represent the means of the treatment. The standard errors of the treatments, when larger than the size of the symbol, are noted along both axes (n ¼ 4).
Distribution of C (mol%)
5 0
20
15
10
5
Axis 2 (19%)
cy19:0
18:1+
18:2ω6,9
18:0
18:1ω9
cy17:0
i17:0
a17:0
16:1+
16:1ω5
16:0
Fig. 4. The mol% distribution of PLFA-C derived from 13C-labeled glucose in soils maintained (a) moist, or (b) dried and rewetted in the laboratory. Continuously moist and drought-prone designations in the legend denote the treatments associated with the 11-year field-level irrigation experiment. Small case letters designate significant differences between the field water treatments and asterisks denote significant differences between the laboratory water stress treatments for that specific PLFA (n ¼ 4, Po0.05, LSD).
0.0
-0.5
10me17:0
0.5
i16:0
i15:0
1.0
a15:0
0
Continuously-moist, moist Drought-prone, moist Continuously-moist, dry-rewet Drought-prone, dry-rewet
-1.0 -1.0
-0.5
0.0
0.5
1.0
Axis 1 (78%) Fig. 3. Differences in the structure of the glucose-metabolizing microbial community associated with the field and laboratory water experiments using a non-metric multidimensional scaling (NMS) analysis of the mol% PLFA-C. The designation noted first in the heading refers to the field manipulation of water, and the designations noted after the comma refers to the laboratory induction of drying and rewetting water stress. Percentages denote the amount of variability associated with each axis. Values of symbols and bars represent means and standard error, respectively (n ¼ 4).
With both types of water stress, whether through natural drought cycles common to tallgrass prairie or through the induction and alleviation of water deficit in the laboratory, there was 25% reduction in the mol% of the fungal PLFA marker (18:2o6,9) compared to situations where
water availability was kept more or less constant. Greater fungal to bacterial biomass ratios were previously reported to occur throughout the growing season as a result of 7 years enhancement of water availability in tallgrass prairie soil (Williams and Rice, 2007). While fungal microorganisms have traditionally been touted as highly resistant to water stress and are known to grow at relatively low water potentials (Harris, 1981; Schimel et al., 1989), these results suggest that perhaps there are groups in soil that may be particularly susceptible to soil water status and stress. Suffice it to say, the ability to grow at low water potential does not necessarily translate into the capacity to withstand the osmotic upshock that follows rewetting of dry soil. Fungal biomass reductions related to drying and rewetting stress have been noted by other researchers (Denef et al., 2001), suggesting that the generalization that fungi are
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relatively resistant to water stress is in need of further verification. In light of the fact that the microbial biomass in the prairie soils are dominated by fungi (Bailey et al., 2002; Williams and Rice, 2007), the reduction in the mol% of the fungal biomarker to water stress, which could suggest fungal turnover resulting from cell lysis, could also be representative of a substantial change in fungal community structure. This would be the case if certain types or groups of fungi were sensitive to osmotic upshock. Unfortunately, PLFA analysis is not capable of resolving these possible differences. In contrast, the bulk of the PLFA, not including the 18:2o6,9 and 18:1o9, are probably most representative of bacterial communities (Bossio and Scow, 1998; Bailey et al., 2002). The lack of significant change in mol% distribution in these PLFA is in agreement with recent reports that bacterial communities in soils appear to be relatively resilient and/or adaptable to the effects of drying and rewetting (Wilkinson and Anderson, 2001; Fierer et al., 2002; Griffiths et al., 2003). Other studies of soil prokaryotic communities suggest that some soil bacterial communities can be sensitive to drying and rewetting (Fierer et al., 2002; Pesaro et al., 2004). However, with these latter studies it is difficult to garner a sense of the magnitude of the community change compared to that of other environmental drivers. In the context of the response of the fungal PLFA (18:2o6,9) to rewetting of dry soil, it was interesting to note that, regardless of treatment, only a small fraction of new C (mol% 1) flowed into this PLFA. This result would seem to suggest that only a small subset of the fungal community responded to the glucose addition. If only a small component of the community was actively growing on the glucose, this limits extrapolation as to how the broader fungal community might respond to water stress. We cannot rule out the possibility, furthermore, that this low response by the fungal community may be analogous to the negative influence that tillage may have on fungal communities (Wardle, 1995). As such, the fungal biomass response to drying and rewetting may have been partially precipitated by the disturbance initiated by the sampling and sieving of the soil, and may have inadvertently increased their susceptibility to water stress and lowered the response of the fungi to glucose addition. While we tried to strike a balance between preincubation of the soils before initiation of the experiment to help offset disturbance effects, we also did not want to over-incubate the soils and risk changing the conditions that might then override or mask the effects manifested in the field experiment. It is also important to note that the degree of drying that we inflicted on the soil and its community members was not a typical yearly drying scenario, but more an extreme that would occur in the driest years, perhaps two to three times per decade (Garcia, 1992; Williams, 2001). Hence, a more typical water deficit in soil may not have the same detrimental effect on the
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fungal biomass. More research using several different levels of water stress and using undisturbed soil will help resolve these questions. By utilizing high-resolution isotope techniques and focusing on the most active, growing, and presumably the most sensitive subset of the community we expected to see changes in the way that the metabolically active community members utilized glucose, a molecule that is constitutively utilized by a widespread set of microorganisms. In this way, for example, we expected to see that some biomarkers, such as those of less dilution stress tolerant gram-negative microorganisms (16:1o7, 18:1o7, cy17:0, cy19:0) to show marked reductions in the amount of glucose-C, while gram-positive types (i15:0, a15:0 i16:0, i17:0) which have been shown to be more water stress tolerant would show definitive increases in glucose-derived C (Harris, 1981; Halverson et al., 2000). However, even with the significant change in the structure of the actively growing microbial community in response to drying and rewetting, there were no specific changes in PLFA, and the structural alterations seemed small and unremarkable compared to the overall similarities in the distribution of glucose-C within the community. In contrast to communities derived from soils in more humid and moist regions, it has been previously hypothesized that communities derived from arid and drymesic type systems, such as the tallgrass prairie, may be naturally resistant and adaptable to drying–rewetting induced water stress (van Gestel et al., 1993; Fierer et al., 2002; Pesaro et al., 2004), a view that is generically supported by our work. The small but structurally similar change in the actively growing community in response to drying and rewetting stress by both field water availability treatments makes sense in light of the soil conditions at sampling. When sampled in late September, the water contents and presumably other environmental factors such as temperature were similar between the continuously moist and drought-prone soils. While it was shown that the structure of the total microbial community with contrasting water regimes are distinctive from each other, the response of the actively metabolizing community may be more closely related to the immediate environmental conditions rather than historical treatment effects. Indeed, previous research that studied the functional response of the cultivable community bears this possibility out (Griffiths et al., 2003; Williams and Rice, 2007). Presuming that the two active microbial communities were similar, it is then no surprise that the drought-prone and continuously moist field soils responded similarly to drying and rewetting induced water stress under laboratory conditions. Based on observations for glucose-responsive community members, and the overall dynamic nature of soil microbial communities related to seasonal influences, the response of the active community members needs further study. Indeed, even the small non-specific change that we
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noted in the flow of C to PLFA may be more indicative of physiological rather than structural community change. However, if it turns out to be a broad truism that microbial community structure does not change or changes very little in response to drying and rewetting induced water stress, then other mechanisms are needed that can account for flushes of C and N that typically follow the wetting of dry soil. One popular hypothesis suggests that microorganisms in soil are responding and adapting to the drying phase of water stress through the accumulation of organic cytoplasmic solutes (alcohols, amino acids). Upon rewetting, these solutes are expelled from the biomass and redistributed into the extracellular soil matrix where they are quickly mineralized (Kieft et al., 1987; Halverson et al., 2000; Fierer and Schimel, 2003). This hypothesis has merit in that a microbial response of this type has been widely measured in cultured systems (Tschicholz and Truper, 1990; Schleyer et al., 1993; Halverson et al., 2000). It also has the advantage of helping to explain both the increase in carbon dioxide and N production rates that typically occur immediately following the rewetting of dry soil. Lastly, it also helps to explain the resilience of the microbial community structure by invoking a known physiological adaptation to sudden and large water potential changes that occur in most soils. This hypothesis does not rule out the possible contributions of non-microbial sources of mineralizable C such as that released through physical slaking or the breakdown of aggregates that have been shown to follow drying and rewetting (Degens and Sparling, 1995; Denef et al., 2001; Cosentino et al., 2006). Indeed, there is still evidence that both microbial and nonmicrobial sources play an important role in contributing to the nutrient flushes released when rewetting of dried soil (Mikha et al., 2005; Wu and Brookes, 2005). The results of this study have interesting implications regarding the mechanisms of community response to drying and rewetting. In the light of other research, and if the broader PLFA results can be said to be representative of the general community response, soil microbial communities as a whole appear to be rather well adapted to water stress. By exclusion this would suggest that process changes (e.g., C and N flushes) that can be attributed to soil biology might be best explained by physiological and functional changes rather than structural changes in communities. However, more research is needed to understand the nature of the microbial, and especially the fungal response to drying and rewetting in soil.
Acknowledgments I appreciate the field and laboratory support provided by Jami Schaffner and Amy Thompson. This research was funded by a competitive grant from the Soil Processes Division within USDA-NRI. Special thanks is extended to the Konza Prairie Biological Station for providing access to their long-term irrigation experiment.
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