RESEARCH ARTICLE
Microbial Community Composition in a Rehabilitated Bauxite Residue Disposal Area: A Case Study for Improving Microbial Community Composition Ronan Courtney,1 Jim A. Harris,2 and Mark Pawlett2,3 Abstract The chemical composition of rehabilitated Bauxite Residue Disposal Areas (BRDA) remains the primary indicator of rehabilitation success, with little consideration of microbial community development. We investigated links between the chemical and microbial components of rehabilitated residue at the Aughinish Alumina BRDA (Ireland). Rehabilitated was compared to unamended residue and to an analogy reference soil from unmanaged grassland within the refinery boundary. Bauxite residue comprised of areas with 1, 11, and 12 years following rehabilitation establishment, and gypsum applied at 45 and 90 t/ha. The unamended residue was typical of bauxite residues with high pH (10), sodicity (exchangeable sodium percentage [ESP]-79), exchangeable sodium (19 cmol/kg), salinity (electrical conductivity [EC] 2.6 mS/cm), and low/negligible nutrient content, microbial biomass (71 𝛍g-C/g), and fungal phospholipid fatty acid (PLF). Microbial biomass increased 10-fold with only 1 year
Introduction The alumina industry produces alkaline bauxite residue as a by-product. Global residue production was estimated at 120 million t/year (Power et al. 2011). The majority of bauxite residue is stored in impoundments called Bauxite Residue Disposal Areas (BRDA). Rehabilitation of residue promotes soil aggregation, thus stabilizing the material and reducing pollution threat, but achieving a sustainable cover remains a challenge due to the residue’s inherent alkalinity (pH 11.3), high sodicity, salinity, and lack of nutrients and structure (Graefe & Klauber 2011; Courtney & Harrington 2012; Courtney et al. 2013). Practices to ameliorate the high alkalinity of bauxite residue include gypsum amendment (e.g. Jones et al. 2010) residue carbonation, seawater neutralization (Menzies et al. 2009) and bacterial amelioration (Hamdy & Williams 2001). 1 Department
of Life Sciences, University of Limerick, Limerick, Ireland
2 School of Applied Sciences, Cranfield University, Bedfordshire, MK43 0AL, 3 Address correspondence to M. Pawlett, email
[email protected]
© 2014 Society for Ecological Restoration doi: 10.1111/rec.12143
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U.K.
of rehabilitation. Gypsum application rate had no effect on microbial biomass. Phospholipid fatty acid analysis (PLFA) demonstrated the emergence of distinct microbial community dependent on rehabilitation time and gypsum application rates. Changes of PLFA profiles were correlated (multiple regressions analysis) to shifts in residue chemical properties (sodicity, organic C, total C, total N, salinity, Mg). An increase of the arbuscular mycorrhizal fungi fatty acid (16:1𝝎5) with reducing pH has implications on rehabilitation practices. The microbial characteristics of the rehabilitated residue were approaching that of a soil from an unmanaged reference site adjacent to the working site. Gypsum affected PLFA properties, and thereby application has implications for rehabilitation success. For successful ecosystem reconstruction, it is critical that rehabilitation practices consider microbial development. Key words: BRDA, gypsum, microbial, PLFA, sodicity.
Gypsum, combined with organic matter (composts) and/or fertilizers, are commonly applied to lower pH and sodicity and improve nutrient status. Current rehabilitation objectives require achieving a pH of less than 9 and exchangeable sodium percentage (ESP) of less than 9.5 (Graefe & Klauber 2011). This can be achieved by applying gypsum at 90 t/ha, which also promotes plant growth (Courtney & Harrington 2012) and microbial activity (Courtney et al. 2011; Schmalenberger et al. 2013). Historically, revegetation and rehabilitation practices focused on improvements of residue chemical composition, with less emphasis on ecosystem development. Mine-site rehabilitation is increasingly moving from vegetation establishment to ecosystem construction (van Hamburg et al. 2004). To achieve this, practices require optimization to improve community establishment for long-term success. Although sodic and saline stress inhibits microbial activity (Rietz & Haynes 2003), there have been relatively few studies of microbial communities in rehabilitated sodic wastes. Schmalenberger et al. (2013) demonstrated that Acidobacteriaceae increased after 12 years of rehabilitation, but this genotypic study was limited to a bacterial assessment. Banning et al. (2011a) found a rapid increase in bacterial and fungal diversity, although this study was limited to sites of ≤3 y rehabilitation. Phospholipid fatty acid analysis Restoration Ecology Vol. 22, No. 6, pp. 798–805
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(PLFA) has been used extensively to observe microbial community shifts following a variety of land management (Bååth & Anderson 2003; Harris 2003; Pawlett et al. 2009; Rousk et al. 2010) and reclamation scenarios such as opencast coal mining operations (Harris et al. 1989), mine tailing covering (Dimitriu et al. 2010), rhizosphere development in acid tailings (Carrasco et al. 2010) and alkaline Cu tailings (Huang et al. 2011), but has not been used to determine effects of amendment and rehabilitation of alkaline, sodic wastes on microbial communities. PLFA profiles represent the in situ whole viable microbial community, and are analogous to the ecological concept of functional groups rather than species (Joergensen & Wichern 2008), and remain a widely used tool for describing microbial community composition (Chowdhury & Dick 2012). This case study investigated the effect of bauxite residue rehabilitation at the Aughinish Alumina BRDA (Limerick) on the whole viable microbial community using PLFA and indicator fatty acids. Through recommendations of McKinley et al. (2005), rehabilitated bauxite residues were compared to an undisturbed grassland reference soil. Shifts in microbial community structure were also linked to changes in key soil chemical properties. We hypothesized that: (1) the rehabilitation practices imposed on the bauxite residue at Aughinish Alumina would alter the microbial community’s phenotypic (PLFA) profile, (2) the shift in the microbial community profile observed would approach that of the community characteristics associated with a local unmanaged grassland soil, (3) the shift in soil microbial community profile will be related to the change in the soils abiotic components. Limitations of case study scenarios are recognized in that they do not present a factorial design; however, knowledge gained will assist in effective ecosystem reconstruction.
Methodology Study Site and Experimental Design
The study area comprised the Aughinish Alumina BRDA and refinery at Limerick, South-West Ireland (lat 52.616078∘ N, long −9.0704155∘ W). The climate is temperate with a 2-year average annual average rainfall of 1,014 mm, and a mean annual temperature of 10.6∘ C (refinery meteorological data). A series of bauxite residue rehabilitation regimes were implemented on the BRDA from 1997 to 2010. Four extant rehabilitated areas were investigated based on the differing gypsum application rates and times since seeding with grass (Agrostis stolonifera, Fescue longifolia, Holcus lanatus, Lolium perenne) and clover (Trifolium repens, T. pratense). Seeding was at 100 kg/ha following a 4-month leaching period. Rehabilitated residue areas comprised: (1) unamended (y0), (2) gypsum applied at 90 t/ha and with 1-year of vegetation cover (y1/G90), (3) gypsum applied at 90 t/ha and with 11 years of vegetation cover (y11/G90), (4) gypsum applied at 45 t/ha and with 12 years of vegetation cover (y12/G45). The rehabilitated areas had also been amended with compost at 120 t/ha. For all rehabilitated sites, amendments were surface spread and incorporated to approximately 0.2 m depth by rotivation and harrowing.
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At seeding, all sites received inorganic fertilizer but not further applications were made since. The bauxite residue rehabilitated treatments were compared to soil samples taken from an adjacent unmanaged grassland reference site (R: lat 52.620950∘ N, long −9.056854∘ W). This site was chosen for the study as it may be regarded as a “target” system condition (Harris 2003, 2009), and it has already been demonstrated that the older sites were physicochemically similar (pH, electrical conductivity [EC], and texture) to this site (Courtney et al. 2013). Rehabilitation trials were initiated on the BRDA in 1998 to investigate methods for amending the sodic and alkaline bauxite residues to support vegetation establishment. Residue disposal and management is within a series of raises (upstream method) and the BRDA is operational. Consequently, available space for rehabilitation work is restricted to terraced areas between raises. All study sites were located on the same BRDA terrace height. Residue rehabilitation areas (approximately 200 m2 ) were divided into grid systems within which five sampling locations of 2 m2 plots were randomly selected. Soils were sampled on 14 June 2011 and within each plot eight random soil cores (2.5 cm diameter; 0–10 cm depth) were obtained and bulked to form a composite sample that was homogenized and sieved ( 0.05) were not affected. The soil pH was reduced compared to the raw residue (at pH 10.42) to 7.89 where 45 t/ha of gypsum was applied, which was still significantly greater than that of the reference soil at pH 7.43 (p < 0.05). Where 90 t/ha was applied the pH was further reduced to 7.81, which was similar to the reference soil (p < 0.05). Total nitrogen was greater where the gypsum was applied at 90 t/ha compared to 45 t/ha, such that at 90 t/ha total N was similar (p > 0.05) to the reference soil (0.52% total N). At 45 t/ha of gypsum, the total N content increased to 0.20% compared to the raw residue that had only 0.03% total N, but was still significantly less than that of the reference soil. Total carbon increased to 2.67% where 45 t/ha of gypsum was applied (y12/G45) compared to 5.90% C with 90 t/ha. However, the rehabilitation practices imposed did not increase total carbon sufficiently to reach values similar to the reference soil, which at 8.87% C was significantly (p < 0.001) greater than all of the rehabilitated soils. Mg was similar to that of the reference soil where gypsum was applied at 45 t/ha; however, where 90 t/ha of gypsum had been applied the Mg content had
Table 1. Chemical parameters (means with standard error [SE]). Raw Residue (y0)
pH ESP (%) Salinity (mS/cm) Na (cmol/kg) K (cmol/kg) Ca (cmol/kg) Mg (cmol/kg) Organic C (%) Total C (%) Total N (%) Textural class
1ya:90 t/hab
11ya:90 t/hab
12ya:45 t/hab
Reference
10.42 (0.01) 79.1 (3.4) 2.6 (0.3) 18.9 (2.1) 0.30 (0.03) 4.5 (0.7) 0.05 (0.02) 0.20 (0.02) 0.61 (0.04) 0.03 (0.00)
8.56 (0.29) 31.8 (5.4) 1.2 (0.4) 7.6 (1.1) 0.17 (0.03) 17.2 (3.1) 0.21 (0.03) 3.56 (0.48) 4.37 (0.44) 0.40 (0.04)
7.81 (0.02) 6.2 (0.6) 0.5 (0.0) 1.3 (0.1) 0.46 (0.09) 17.9(1.1) 1.26 (0.10) 3.22 (0.52) 5.20 (0.25) 0.42 (0.02)
7.89 (0.08) 9.1 (0.8) 0.2 (0.0) 1.1 (0.1) 0.41 (0.04) 9.9 (0.5) 0.59 (0.10) 2.59 (0.52) 2.67 (0.49) 0.28 (0.05)
7.43 (0.10) 0.6 (0.1) 0.3 (0.0) 0.1 (0.0) 0.23 (0.02) 18.3 (0.7) 0.52 (0.02) 2.46 (0.05) 8.87 (0.14) 0.53 (0.01)
Silty clay
Sandy loam
Sandy loam
Sandy loam
Sandy loam
Values are means with SE in parentheses. Salinity as electrical conductivity. a Number of years vegetation cover. b Gypsum application rate.
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1800
Biomass-C (µg/g)
1600
c
1400 1200 1000
b
800
4
b b
2
600
0
400 0
a y0
y1/G90
y11/G90 Site ID
y12/G45
R
-2 -4 -6 -8 - 10 5
4
3
2
PC
1
0
2
9% (1
Figure 1. Change in microbial biomass with rehabilitation. Data are means (error bars represent SE, n = 5) of raw residue (y0), 1y rehabilitation with 90 t/ha gypsum (y1/G90), 11y rehabilitation with 90 t/ha gypsum (y11/G90), 12y rehabilitation with 45 t/ha gypsum (y1/G45), and the reference soil (R). Letters a, b, and c represent significant groupings (p < 0.05) by post hoc Fisher.
PC 1 (46%)
200
)
increased to a concentration (1.26 cmol/kg) that was significantly greater than that of the reference soil. The concentration of Ca increased to values similar to the reference soil after only 1 year (4.5 to 17.2 cmol/kg). However, where only 45 t/ha of gypsum was deployed, the Ca content had only reached 9.9 cmol/kg, which was significantly less that where 90 t/ha gypsum had been applied and less than that of the reference soil (Table 1). Various other chemical parameters analyzed reached values (p > 0.05) similar to that of the reference soil. Soil organic C required only 1 year of rehabilitation, whereas salinity and Na required 11 years. The concentration of K in the unamended residue was similar to that of the reference soil prior to the rehabilitation procedures. Sodicity reduction with rehabilitation was not sufficient to reduce to that of the reference soil (Table 1). Microbial Properties
After 1 year of rehabilitation, and 90 t/ha gypsum, the microbial biomass increased from 71 (raw residue) to 842 μg-C/g. There were no further increases of microbial biomass irrespective of the increased time since rehabilitation or altering the gypsum application. The microbial biomass of the reference soil was significantly greater than all rehabilitated sites, with a microbial biomass of 1,486 μg-C/g (Fig. 1). The first three principal components (PC) of the PCA generated from PLFA data together accounted for 75% of the total variation, with significant (p < 0.001) effects on all three axes (Fig. 2). PC1 separated the unamended residue (y0) from all other locations, which were indistinguishable. PC2 further separated the sites, with both the reference (R) and 1-year (1y/G90) soils forming significantly distinct groups, whereas the 11-year (11y/G90) and 12-year (12y/G45) soils remained grouped together. However, the 11-year (11y/G90) site was significantly distinct from the 12y/G45 site on PC3. Fatty acids with a positive loading (>0.8) on PC1 included: i16:0, ai16:0, 16:1𝜔5, cyc17:0, 18:1𝜔9c. Fatty acids with a negative loading
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-1
-2
-3
-4
- 5 -3
-2
-1
0
P
1
2
3
4
%) (11 3 C
Figure 2. PCA score plot of ordination means showing the effect of rehabilitation on the PLFA phenotypic profile. Triangle, reference soil; square, raw residue (y0); circle, 1 year rehabilitation with 90 t/ha gypsum; diamond, 11 years rehabilitation with 90 t/ha gypsum; cross, 12 years rehabilitation with 45 t/ha gypsum.
(0.8) to PC2 (17:0 isomer), and one fatty acid contributed (>0.8) to PC3 (ai15:0). Comparison of the PC scores with the soil chemical data (Table 2) demonstrates that PC1 was highly correlated (p < 0.01) with soil Ca, Mg, Na, ESP, pH, EC, total C, total N, and organic C contents. PC2 was correlated (p < 0.05) with total C, and PC3 with Mg. Multiple regression analysis of the PC scores demonstrates that PC1 (r2 = 0.885), PC2 (r2 = 0.834), and PC3 (r2 = 0.666) can be predicted (p < 0.001) from the soil chemistry data (Equations 1–3) following the linear equation of y = 𝛼 + 𝛽⋅x (where y is the PC score and x is the predictor). PC1 = 0.685 − (0.081 × ESP) + (0.78 × Org C) + (0.928 × EC)
(1)
PC2 = 1.17 − (−3.31 × Mg) + (−2.26 × total C) + (32.16 × total N)
PC3 = 3.63 − (4.73 × Mg) + (0.05 × ESP)
(2)
(3)
PLFA signature biomarkers were affected (p < 0.001) by rehabilitation (Table 3). Relative proportions of the fungal, total bacterial, AM, and Gram-positive PLFAs were significantly increased after 1 year of rehabilitation in comparison to the unamended residue (y0) to levels greater than that of the reference
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Table 2. Pearson product moment coefficient showing the correlations (r) between the PLFA PC scores and chemical parameters. PC1
K (cmol/kg) Ca (cmol/kg) Mg (cmol/kg) Na (cmol/kg) Sodicity (%) pH Salinity (mS/cm) Total C (%) N (%) Org C
PC2
PC3
0.0413
−0.147
NS
NS
NS
−0.008
0.115
0.690 ∗∗∗ 0.554 ∗∗ −0.899 ∗∗∗ −0.918 ∗∗∗ −0.907 ∗∗∗ −0.776 ∗∗∗ 0.687 ∗∗∗ 0.761 ∗∗∗ 0.730 ∗∗∗
0.402
NS
NS
−0.232
0.654 ∗∗ −0.019
NS
0.236 NS
NS
0.278
−0.017
NS
NS
0.265
0.041
NS
NS
0.211
0.059
NS
NS
−0.448 ∗ −0.171
0.011 NS
0.215
NS
NS
0.319
0.116
NS
NS
***p < 0.001; **p < 0.01; *p < 0.05. NS p > 0.05.
soil. In addition there was an increase in the fungal/bacterial PLFA ratio. However, Gram-negative PLFAs were reduced in comparison to the unamended residue site, and to levels that were less (p < 0.05) than that of the reference soil. There was no change in Gram-negative PLFAs after 1 year of rehabilitation. The increase in the fungal PLFA and fungal/bacterial ratio seen after 1y rehabilitation remained elevated after 12 years where 45 t/ha of gypsum was applied (y12/G45), but where 90 t/ha of gypsum was applied (11y) the relative proportions of the fungal PLFA and the fungal/bacterial ratio were significantly less than that of the reference soil. Conversely, the increase of both the total bacterial PLFA and Gram-positive bacterial PLFA biomarkers was sustained after 11 years where 90 t/ha was applied with 1y of vegetation cover, but where 45 t/ha of gypsum was applied (12y) both of these PLFA indicators were reduced to values that were significantly similar to the reference soil. There were no further effects on the PLFA marker 16:1𝜔5 after 1-year rehabilitation.
Discussion The unamended residue was typical of bauxite residue (Banning et al. 2011a; Graefe & Klauber 2011) with alkaline pH (10.4), sodic (ESP 80), moderately saline (2.6 mS/cm), very low organic carbon (0.2%), microbial biomass (71 μg-C/g), and nutrient contents. Applications of gypsum at 2% v/v rapidly (6–13 weeks) decrease residue sand pH and sodicity (Jones et al. 2010). Our research demonstrates that similar improvement occurred in rehabilitated residue mud, possibly due to further leaching, microbial action and/or production of organic acids in the rhizosphere.
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Microbial biomass increased to 842 μg-C/g soil after 1 year, but did not recover to that of the reference soil within the 12 years rehabilitation. Where organic matter was not incorporated into bauxite residue rehabilitation process (Banning et al. 2011a), biomass remained at approximately 40 μg-C/g after 2–3 years. The increase of microbial biomass in rehabilitated mine sites with soil Ctot and Ntot (Banning et al. 2011b) demonstrates the importance of incorporating organic matter. The increase of organic C to 3.56% after 1 year rehabilitation was higher than reported by Jones et al. (2010), with increases to 1.5% organic C following application of organic matter at up to 80 t/ha. Higher amounts in our study are possibly due to the higher organic matter input and accumulated C from soils processes. Although recently amended residues have a greater labile carbon pool (Courtney et al. 2013), older rehabilitated residues had significantly higher recalcitrant soil C. We also found ESP values in sites y11/G90 and y12/G45 to be lower than the ESP (15– 19%) reported by Jones et al. (2010). Microbial biomass, respiration, and growth are inhibited in soils with high Na content, possibly due to sodic soil processes such as dispersion (Rietz & Haynes 2003; Wong et al. 2008). The combined effect of rehabilitation practices affected the soil microbial community’s phenotypic (PLFA) profile, with increasing similarity compared to the reference soil. The microbial community of the 12-year rehabilitated residue where gypsum was applied at 45 t/ha was more similar to the reference soil than the 11-year site with gypsum applied at 90 t/ha. Schmalenberger et al. (2013) also found that the rehabilitation practices imposed at the Aughinish Alumina BRDA improved the bacterial community structure such that it more closely represented unmanaged grassland soils, but conversely the higher gypsum application rate (45 t/ha compared to 90 t/ha) favored the establishment of a bacterial community. Differences may be methodological (bacterial DNA vs. whole community PLFA) and/or due to the selection of the reference site. In this study the reference site was local to the Limerick BRDA, whereas in Schmalenberger et al. (2013) the reference was not local. The relationship between improvements in the residue’s abiotic characteristics was compared to the microbial (PLFA PCA) phenotypic profile. PC1 was positively correlated (Pearson coefficient) with exchangeable cations (Ca2+ , and Mg2+ ), total C, and total N, and negatively correlated with exchangeable Na, sodicity, pH, and salinity. In addition, total carbon was positively correlated with PC2, and Mg2+ to PC3. Multiple regression analysis demonstrated the relationship between the abiotic and biotic components as PC1 can be predicted from sodicity, organic C contents, and salinity (Equation 1). Improved resolution of this prediction can be provided using the soil’s Mg, total C, and total N contents (PC2: Equation 2) and Mg and sodicity (PC3: Equation 3). Sodicity and high pH of bauxite residue are likely to inhibit microbial growth and activity (Rietz & Haynes 2003) and consequently improvement of these conditions would reduce microbial stress. Other studies have demonstrated the effect of pH on soil PLFA profiles, but these have been for pHs ranging from acidic to slightly alkaline (pH 3–8) (Bååth &
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Anderson 2003; Pawlett et al. 2009; Rousk et al. 2010). This research demonstrated that the reduction of pH in alkaline bauxite residues affects the microbial community phenotypic profiles PC1 scores. Sodic soils are characterized by high exchangeable Na and ESP, both of which were negatively correlated (Pearson coefficient) with PC1. Grayston et al. (2004) found negative correlations between microbial fatty acids and soil exchangeable Na, and positive correlations with exchangeable Ca (over a pH range of 4.1 to 6.5). The restricted nutrient pool (carbon and nitrogen) of residue microbial community is likely to increase microbial physiological stress. Management regimes that improve the soil nutrient status would improve the functional capacity of the soil microbial system, and hence improve nutrient cycling processes. The proportions (mol%) of fungal PLFA increased dramatically after only 1 year. Increases in soil fungal biomass are often associated with increases in total C (Bååth & Anderson 2003; Frouz et al. 2006) and increased soil particle size distributions with small particle size favoring bacterial over fungal communities (Sessitsch et al. 2001; Carrasco et al. 2010). Field-scale amendment of bauxite residues with composts provides recalcitrant carbon sources, leading to improved soil nutrient status and particle size distributions that would inevitably increase fungal biomass. The increase in fungal biomass associated with bauxite rehabilitation in this study was sustained where 45 t/ha of gypsum was applied (12y), but not where 90 t/ha of gypsum was applied (11y). Effects of acidic pH on fungi are well documented, with little information of the effects of alkaline conditions. In a study of arable soils with pH up to 8.3, the fungal PLFA marker 18:2𝜔6,9 did not show a clear trend with pH (Rousk et al. 2010). Thereby trends associated with fungal biomass in alkaline soils merit further investigation. Increases in soil fungal:bacterial ratios in grasslands reflect enhanced ecosystem efficiency (Bardgett & McAlister 1999). The increased fungal:bacterial ratio with rehabilitation suggests a system with improved nutrient cycling. Indeed, two of the soil locations (y1/G90and y12/G45) had fungal:bacterial ratios higher than that of the reference soil. This suggests that rehabilitation may have improved ecosystem efficiency to greater than that of the selected reference soil. Improvements in plant diversity can also affect fungal:bacterial ratios on reclaimed mine wastes (Carrasco et al. 2010). Although plant diversity was not assessed in this study, increases in plant diversity were previously recorded for these sites (Courtney et al. 2009).
The AM fungi bioindicator (16:1𝜔5) substantially increased after only 1 year of rehabilitation, to a level that was sustained for 12 years. Although caution must be stressed when interpreting the relevance of these data as 16:1𝜔5 is also present in some bacteria (Frostegård et al. 2011), its use may provide a focus for further investigation. Alkalinity, salinity, and low soil nutrient levels are the most probable causes of stress to AM fungi (Oliveira et al. 2005). Intervention to reduce pH stress increases the AM fungi biomarker16:1𝜔5 (Frostegård et al. 1993; Pawlett et al. 2009). Increased AM fungi in the residue sites are beneficial for sustained plant growth. Babu and Reddy (2011) found that inoculation with AM fungi increased the growth of Bermuda grass (Cynodon dactylon) in bauxite residues. Gram-negative bacteria was higher (mol%) in the raw residue. Schmalenberger et al. (2013) identified Gram-negative bacteria Bacteriodetes (Chitinophagaceae) and Proteobacteria (several species) from the raw residue only. Tscherko et al. (2004) observed decreases in Gram-negative bacteria during ecosystem development toward mature grassland and attributed this to a shift from chemolithotrophic to heterotrophic communities with increasing carbon input. Similarly, changes in microbial communities as evidenced in this study are attributed to improved abiotic conditions. Implications for Practice • Rehabilitation strategies employed were sufficient for colonization by a complex microbial community structure. • Shifts in the microbial community composition were linked to improvements in the soils abiotic component. • Direct observation of microbial systems provides a more precise description of the soil microbial community rather than using indirect observations by soil chemical parameters. • Gypsum application rate affects the microbial community composition, with implications for ecosystem recovery. • Rehabilitation practices should consider amendment procedures to optimize improvements in the soil microbial community to promote sustainable ecosystem establishment. Acknowledgments The authors would like to acknowledge Aughinish Alumina Ltd. for their financial and technical support, and to the UL seed funding program.
Table 3. Mean relative abundance (mol%) of selected signature fatty acids, fatty acid ratios of microbial PLFA. Location ID
y0 y1/G90 y11/G90 y12/G45 R
AM Fungi (16:1𝜔5)
Fungi (18:2𝜔6,9)
Bacterial FA
Fungi to Bacterial Ratio
Gram+ FAs
MUFA (Gram−)
1.4 (0.1) 8.2 (0.4) 8.3 (0.3) 7.5 (0.2) 5.6 (0.1)
0.6 (0.1) 10.7 (0.6) 3.9 (0.3) 10.6 (0.8) 6.4 (0.3)
18.8 (1.6) 30.2 (0.6) 30.4 (0.5) 24.7 (0.8) 24.2 (0.6)
0.03 (0.01) 0.36 (0.03) 0.13 (0.01) 0.43 (0.04) 0.27 (0.01)
10.6 (0.6) 14.4 (0.3) 15.9 (0.3) 11.6 (0.4) 11.8 (0.4)
30.1 (3.6) 14.8 (0.5) 12.3 (0.3) 10.7 (0.3) 10.6 (0.4)
Figures in parentheses represent standard error (n = 5). FA, fatty acids; MUFA, monounsaturated fatty acids; Gram+, iso and anteiso FAs; y0, raw residue; y1/G90, 1y rehabilitation with 90 t/ha gypsum; y11/G90, 11y rehabilitation with 90 t/ha gypsum; y12/G45, 12y rehabilitation with 45 t/ha gypsum; R, reference site R.
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