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Biochemical properties of highly mineralised and infertile soil modified by acacia and spinifex plants in Northwest Queensland, Australia.


In many remote regions of Australia (such as Mt Isa and Cloncurry, North-west Queensland) where base metal mines (e.g. Cu, Pb-Zn mines) are located, the lack of adequate volumes of topsoil to cover large area of mined landscapes (e.g. 100s-1000s hectares of waste rock and tailings dams) has made necessary to engineer growth media and root zones for revegetation purposes (Huang et al. 2014). Wrong choices of engineering options such as the common practice of applying high rates of N and P inputs via (in)organic fertilisers in root zones would result in significant deviation of developmental trajectory of revegetated plant communities from the expected, in terms of species diversity and weed competitions (as we have observed in field trials at Mt Isa Mine) (Huang et al. 2011, 2012). This is because there is a close feedback between soil and plant systems in terrestrial ecosystems through linkages of functional microbial community and associated biochemical processes (Kardol et al. 2010; Wardle et al. 2004). High fertility in root zones favour forest and crop species of high productivity (Liu et al. 2012; Waldrop et al. 2000), while slow-growing native plant species with low productivity and low nutrient requirements dominate infertile and arid landscapes (Bums et al. 2013). Soil biochemical properties and key biological processes (e.g. organic matter decomposition, nutrient cycling) (Caravaca et al. 2005; Marschner et al. 2001) in the root zone are results from the long-term plant colonisation through species-specific litter feedback and root zone modification (Quideau et al. 2001). Therefore, understanding physicochemical and biochemical properties in soils colonised by the keystone native plant species in target plant communities will provide benchmarks for engineering growth media and root zones when rehabilitating mined lands.

At Mt Isa, North-west Queensland where many copper-gold (Cu-Au) and lead-zinc (Pb-Zn) mines are located, native plant communities distributed in colluvial plains are dominated by slow-growing and water-nutrient efficient spinifex and acacia species (Specht and Specht 1999; Fox etal. 2001), due to their highly adaptive ecophysiological traits in infertile and arid landscapes (Diagne et al. 2013; Reid and Hill 2013). For example, Chisholm's Wattle (Acacia chisolmii, [C.sub.3] plant, [N.sub.2]-fixing legume shrub) and Spinifex (Triodia spp., [C.sub.4] grass) are two keystone native plant species widely present on stony and lateritic soils in the colluvial and well drained land of Mt Isa region (North-west, Queensland, Australia) (Specht and Specht 1999; Fox et al. 2001). Leguminous species (e.g. Acacia spp.) are critical N sources in infertile soil systems (Wardle etal. 2004). In addition, legume-microbes interactions have been observed for Acacia spp. with abundant propagules, AM hyphae and infectivity, which are not common for spinifex (Jasper et al. 1989). Spinifex with unique drought adaptive leaf anatomy is tolerant of high temperature and radiation and extreme water deficit conditions (Winkworth 1967). The canopy characteristics and physiological traits of these species are ideal for phytostabi rising mined land under semiarid climatic conditions (Murphy et al. 2010; Nicholas et al. 2009). However, the lack of information about biogeochemical properties of natural soils colonised by target native plant communities hinders decision-making at local base metal mines (such as Mt Isa Mines), about growth media and root zone reconstruction options in rehabilitation programs.

The present study is aimed at characterising physicochemical and biochemical properties in infertile soils colonised by the acacia (A. chisholmii) and spinifex (T. pungens) species in a colluvial plain at George Fisher, Mt Isa, North-west Queensland, Australia, in order to engineer growth media to support similar plant species and communities to be rehabilitated across mined landscapes. It aims to investigate species-specific differences of microbial biomass, structure (PLFAs profile) and functions (respiration, mineralisation, enzymatic activities) in root zone soils in the native plant community. Carbon (C) isotope signature of plant litters and soil organic carbon (TOC) were used to confirm species' contribution to TOC over long periods (Dalai et al. 2005). The analysis of community-level phospholipid-derived fatty acids (PLFAs) profiles (Zelles et al. 1992) and enzymatic activities (Badiane et al. 2001) was conducted to characterise biochemical properties of soils colonised by the two native species. Possible associations were explored between the physicochemical properties and microbial community structure and functions in root zone soils. The expected findings about the biochemical properties and processes in natural soils colonised by native plant species, will aid decision-making in engineering growth media and root zones (such as fertility management and amendment options), which are consistent with ecophysiological requirements of these native plant species for phytostabilising mined land at mine closure.

Materials and methods

Site description and sampling

Mt Isa (20.73[degrees]S, 139.5[degrees]E) is located in North-west Queensland, Australia. Local climatic conditions can be found at Australian Metrological Bureau ( In summary, its climate can be classified as subtropical and semiarid, with annual pan evaporation of 2800 mm and average annual rainfall of 427 mm, and average yearly temperature of 25.5[degrees]C (19-32[degrees]C). Local rainfalls are highly variable between wet season (during November to February) and dry season and can vary significantly from year to year. For example, above average rainfalls were recorded for the years 1991 (618 mm), 1997 (799 mm) and 2011 (1113 mm), but as low as 201mm in 2008. Plant and soil sampling was conducted in February 2013 when there was monthly rainfall of 90.9 mm and average temperature of 23.7[degrees]C (Bureau of Meteorology 2013).

The soil in the region is classified as Rudosols (Isbell 2002). Soils are shallow red duplexes, red-brown loams and red earths (Christian et al. 1954). The dominant vegetation in Mt Isa area is low open woodland (Eucalyptus-Acacia) in combination with open hummock grassland (Triodia pungens) (Perry et al. 1964).

Soil and plant samples were collected from a selected area of 50 x 70 m at George Fischer colluvium plain with similar topographic feature to Mt Isa Mine tailings landscapes, ~26 km north of the Mt Isa Mine tailings impoundments. Two transacts of 30 m length with dominant species stands were chosen for each species. The distance between the two transacts was maintained at least 20 m apart from each other. Three representative sites (30 x 30 cm quadrat under dense species stand) along each transact were sampled for soil and litters beneath mono-dominance stands of acacia (A. chisholmii) and spinifex (T. pungens), respectively. Plant litters and the corresponding surface soil at the depth of 0-5 cm was sampled within each quadrat. At each site, 3 representative subsamples of soil were taken across each quadrate and pooled into a composite sample which was evenly divided into two sets of subsamples. One set of subsample was placed in sealed plastic bags, transferred within a precooled container with ice-packs (< 10[degrees]C) from the field to the mine-site laboratory within 3 h after sampling and stored at 4[degrees]C before transportation back to CMLR laboratory. These samples were then dried at 40[degrees]C and sieved <2 mm for physicochemical analyses. The other set was snap-frozen in liquid nitrogen in the field, transported back to the laboratory in a cryo-shipper and freeze-dried before PLFA analysis. Plant materials were rinsed in 3 changes of deionised water and dried at 65[degrees]C until a constant weight and ball milled for further analysis.

Plant analysis

Total organic carbon (TOC) and nitrogen (TN) concentrations of the plant litter samples were determined by dry combustion method with a LECO CNS-2000 analyser (LECO Corporation, MI, USA). Aliquots (0.3-0.5 g) of milled plant samples were digested in concentrated nitric acid by open-vessel microwave method (Milestone Start D) (Huang et al. 2004). Total phosphorous (TP) was analysed by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES, Perkin Elmer Optima 3300 DV, USA). A standard reference plant material (ASPAC 61, Canola leaf, Australian Soil and Plant Analysis Council) was used to verify the accuracy of plant analysis with 90 [+ or -] 10% recovery.

The ratio of isotope [sup.13]C to [sup12]C ([delta][sup.13]C) was analysed by continuous flow isotope ratio mass spectrometry (CF-IRMS, Tracer Mass, Europa Scientific, Milan, Italy). Solid-state cross-polarisation magic angle spinning [sup.13]C nuclear magnetic resonance (CP/MAS [sup.13]C-NMR) for plant litter was done using A Bruker Advance 300 high-resolution NMR spectrometer interfaced to a 7.05 Tesla ULTRASHIELD bore magnet system. Scans between 4 and 10 K were collected and the spectra were plotted between -15 and 265 ppm. Spectral peaks were assigned to four main chemical shift regions: alkyl C (0-50ppm), O-alkyl C (50-110ppm), aromatic C (110-160ppm) and carboxyl C (160-210ppm) (Webster et al. 2000). In general, Alkyl C represents lipids and other aliphatics, whereas O-alkyl C represents more labile carbohydrates such as cellulose (Mathers et al. 2007). Relative intensity for each region was determined by integration using the Varian NMR software package (Version 6. lc, Varian Inc., Palo Alto, CA). Areas of each chemical shift regions were measured and calculated as percentage of the total area.

Soil physicochemical analysis

Water holding capacity (WHC) was determined by the method from Wang et al. (2003). Soil pH, electrical conductivity (EC), and cation exchange capacity (CEC) were measured according to Rayment and Lyons (2011). TOC and TN concentrations in soils were determined as described above, except that samples were checked with hydrochloride acid (HCl) for the presence of carbonate before LECO analysis. The [delta][sup.13]C values in soil were measured by CF-IRMS (Tracer Mass, Europa Scientific). Total concentrations of P, Cu, Pb and Zn in soil samples were measured by ICP-OES (Perkin Elmer Optima 3300 DV, USA) after aqua-regia digestion. A standard reference soil material (SRM 2711a Montana soil, National Institute of Standards, USA) was used to verily the accuracy of metal determinations with recovery ranging 90 [+ or -] 10%.

Water-soluble organic carbon (WSOC) was extracted by shaking pre-incubated soil (adjusted to 50% WHC and incubated for 24 h) in deionised water. The suspension was then centrifuged at 4000 rpm for 10 min and filtered through a 0.45 pm glass-fibre filter. Hot water extractable organic carbon (HWOC) was extracted according to Sparling et al. (1998). In brief, 10 g air-dried sample was saturated in 20 mL cold water (20[degrees]C) for 30 min. The supernatant solution was then discarded and the change of sample weight was recorded to correct the actual sample:water ratio applied for hot water extraction. The mixture of sample and deionised water with a ratio of 1:2 was incubated in water bath at 80[degrees]C for 16 h, which was then centrifuged at 4000 rpm for 10 min and filtered through 0.45 [micro]m glass-fibre filter. WSOC and HWOC was determined by dichromate digestion method (Bremner and Jenkinson 1960).

Bioavailable organic carbon (Bioavailable OC) was determined using the incubation method (Chen et al. 2004). In brief, aliquots of 50 g soil were adjusted to 50% WHC and incubated aerobically at 25[degrees]C for 28 days. All containers were covered with plastic film perforated with several pinholes for gas exchange but avoiding rapid water loss. Deionised water was added to the mixture every 3-4 days during incubation to compensate for water loss via evaporation. Samples were placed in a closed chamber attached with infrared gas carbon dioxide (C[O.sub.2]) analyzer (Q-Box SRI LP soil respiration package, Oregon, Canada). The gas accumulated in the chamber was collected twice per second for 10 min for the analysis of C[O.sub.2] concentrations. The respiration rate was calculated as the change of mg C[O.sub.2]-C [kg.sup.-1] [h.sup.-1]. Tests were conducted at 1, 3, 7, 14, 21 and 28 days of incubation. The bioavailable OC was estimated by calculating the cumulative production of C[O.sub.2] from soils during 28 days incubation.

Estimation of plant derived organic carbon in soil

Soil OC derived from the acacia species ([C.sub.3]) and spinifex species ([C.sub.4]) was estimated from the soil [delta][sup.13]C values by a mixed model mass balance following the equations below (Balesdent et al. 1996).


Soil [C.sub.3] derived C = TOC - Soil [C.sub.4] derived C (2)

where [delta][sup.13][C.sub.soil] is the [delta][sup.13]C value of TOC, and [delta][sup.13]C [C.sub.C4] and [delta][sup.13][C.sub.C3] arc the [delta][sup.13]C values of the pure [C.sub.4] and [C.sub.3] plant litter at the study site, respectively.

Microbial biomass, basal respiration and net mineralisation rate

Microbial biomass was determined by extraction method using a pair of air-dried samples with and without chloroform fumigation (Jenkinson and Powlson 1976). Soil samples were adjusted to 50% WHC and incubated at 25[degrees]C for 7 days. OC in the extract was determined using the same method as for water extract. Microbial biomass carbon (MBC) was calculated as the difference of OC between fumigated and unfumigated samples with a conversion factor KEC as 0.38 (Vance et al. 1987). Microbial biomass nitrogen (MBN) was calculated as the difference of ninhydrin-N between fumigated and unfumigated samples with a conversion factor [K.sub.EN] as 0.54 (Joergensen 1996).

Basal respiration and net mineralisation rates were used as key indicators of microbial activity in the soil. Basal respiration rate was calculated as the average C[O.sub.2] evolution rate during 28 days of incubation. A set of corresponding subsamples were incubated for estimating mineralisation rate. Samples were taken at day 0 and 28 after commencing incubation and analysed for mineral N, which was the sum of ammonium-N (N[H.sub.4]-N) and nitrate-N (N[O.sub.3]-N) in 2M potassium chloride extract. NH4-N in the extract was measured with indophenol blue method (Verdouw et al. 1978). The N[O.sub.3]-N in the extract was measured with salicylic acid colourimetric method (Cataldo et al. 1975), and expressed on an oven dry (105[degrees]C) weight basis. The net mineralisation rates were calculated based on the differences of mineral N in the extract between the end (28 days) and the beginning of incubation (0 days).

Enzyme assays

The activities of four soil enzymes, dehydrogenase, invertase, urease and neutral phosphatase, were chosen as key indicators in this study. Dehydrogenase activity was measured using incubation method (Serra-Wittling et al. 1995). In brief, aliquots of 2 g samples were incubated with 2mL of 0.5% 2, 3, 5-triphenyl-tetrazolium chloride (TTC) and 2mL of Tris-HCl buffer (0.5 M, pH 7.6) for 2 h at 30[degrees]C in the dark. Meanwhile an aliquot of each sample was sterilised by autoclaving as a paired blank. Immediately after incubation, the triphenyl formazan (TPF) formed was extracted with 100 mL of methanol by shaking vigorously for 1 min and measured spectrophotometrically at 485 nm using methanol as a blank. Dehydrogenase activity ([micro]g TPF [g.sup.-1] [h.sup.-1]) was calculated as the difference between unsterilised and sterilised samples. Invertase activity was determined using sucrose as the substrate (Frankeberger and Johanson 1983). Briefly, 0.4 mL of toluene was added to 2 g soil sample and allowed to stand for 15 min, which was followed by adding 2 mL of 10% sucrose and 2 mL acetic acid buffer (0.2 M, pH 5.5). The mixture was incubated for 24 h at 37[degrees]C and then diluted to 100 mL with distilled water. After filtration, reducing sugars in 1 mL of filtrate was measured using a molybdenum-blue method (Gusakov et al. 2011). Invertase activity ([micro]g reducing sugar [g.sup.-1] [h.sup.-1]) was calculated as the difference in reducing sugar concentrations between the substrate induced samples and a blank control. Urease activity was determined with urea as substrate (McGarity and Myers 1967). Briefly, 0.4 mL of toluene was added to a 2 g sample and allowed to stand for 15 min, which was followed by adding 2 mL 10% urea solution and 2 mL citric acid buffer solution (1 M; pH 6.7). After incubation at 37[degrees]C for 24 h, the mixture solution was diluted to 100mL with distilled water, which was immediately filtered. The ammonium product in the filtrate was quantified colourimetrically by using the indophenol-blue method (Ivancic and Degobbis 1984). Urease activity was calculated from the difference in ammonium concentration between that produced from the substrate-induced and the initial value. Neutral phosphatase activity was assessed by the disodium phenyl phosphate method (Shen et al. 2006). Briefly, 0.4 mL toluene was added to 2 g of sample and allowed to stand for 15 min, which was followed by adding 2 mL of 0.5% (w/v) disodium phenyl phosphate and 2 mL of citric acid buffer (0.2 M, pH 7.0). After incubation for 24 h at 37[degrees]C, the mixture solution was diluted to 100mL with 38[degrees]C distilled water and filtered. The filtrate was further diluted 5 times with distilled water, to which 4mL of borate buffer (0.05 M, pH 10), 0.5 mL of 2% 4-amino antipyrine and 0.5 mL of 8% potassium ferricyanide were added. The absorbance of the reaction solutions was measured spectrophotometrically at 510nm. Neutral phosphatase activity was calculated as the difference of phenol formed between the substrate-induced sample and the blank (sample free control).

Microbial community using PLEA analysis

The liquid nitrogen frozen soil samples were freeze-dried before PLFAs extraction (Bossio and Scow 1998). Briefly, soil was extracted in a single-phase mixture of chloroform, methanol and 0.05 M phosphate buffer (pH 7.4) at the ratio of (1: 2: 0.8 v/v/v) from 5 g soils. Phospholipids were separated from neutral lipids and glycolipids on solid phase extraction column (SPE-SI; Bond Elute, Varian, Palo Alto, USA) by eluting neutral lipids and glycolipids with 5 mL chloroform and then 10mL acetone. Polar lipids were eluted with 5 mL methanol, and dried under nitrogen gas at 32[degrees]C. Afterwards, samples were subject to mild alkaline methanolysis by methanol-toluene mixture and potassium hydroxide (KOH). Resulting phospholipid fatty acid methyl esters (PLFA-ME) were extracted with hexane and acetic acid. Prior to analysis with gas chromatography-flame ionisation detector (GC-FID) (Agilent Technologies, Santa Clare, USA), HP Ultra 2 column, hexane containing methyl nonadecanoate fatty acid (19:0) were added as the internal standard. To identify the PLFA-ME, the gas chromatograph was coupled to an ion trap mass spectrometer (GCQ, Thermoquest, Germany). After measurement all values were corrected for the methyl carbon. Standard fatty acid nomenclature was applied (Frostegard et al. 1993). Individual PLFA biomarkers were used to quantify relative abundance of specific microbial groups. The abundance of individual PLFA was determined as nmol per g soil. Concentrations of each PLFA were calculated based on the 19:0 internal standard concentration. In this study, representative fatty acids for typical microbial community were summarised as follows (Baath and Anderson 2003; Frostegard and Baath 1996): A set of fatty acids represented bacterial PLFAs, including 14.0, 15:0, il5:0, al5:0, 16:0, i16:0, 16:l[omega]7c, al7:0, i17:0, br 17:0, cyl7:0, 18:l[omega]7c and cyl9:0. Sum of i15:0, al5:0, i16:0, al7:0, i17:0 and brl7:0 was used an indicator of gram-positive (G+) bacteria. Gram-negative (G-) bacteria were identified by the PLFAs: 16:1[omega]7c, cy17:0, 18:1[omega]7 and cy19:0. The fungi was identified using the PLFAs 18:2[omega]6,9c, 18:1[omega]9c and 18:l[omega]9t. PLFAs 16:l[omega]5c, which were used as a biomarker for arbuscular mycorrhizal fungi (AMF). The actinomycetes were identified by the PLFAs 10Me 18:0. Other PLFAs such as 11 : 0, 18:0, and 10Me 19:0 were also used to analyse the composition of microbial community. Taken together, all of the PLFAs indicated above were considered to be representative of the total PLFAs of soil microbial community (Zelles et al. 1992) (see Supplementary Materials table 1 as available at journal's website).

Statistical methods

Primary data processing was performed using Microsoft[R] Excel. One-way ANO VA was carried out after normality check to test differences between acacia and spinifex on general plant chemistry, soil physicochemical properties, OC and N fractions, microbial properties, PLFAs biomarkers and enzymatic activities in the soils. Means were compared using the Tukey honest significant difference (HSD) test at P=0.05. All statistical analyses were conducted using the SPSS software package (SPSS Statistics 20.0, Chicago, IL, USA).

Redundancy analysis (RDA) were made using CANOCO software for Windows 4.5 (Biometris-Plant Research international, Wageningen, The Netherlands). RDA-environment analysis was performed for microbial community composition (relative abundance of individual PLFAs, expressed as % mol of the total) and environmental variables (including soil and litter parameters). RDA-function analysis was for linkage between microbial structure (abundance of individual PLFAs) and functions (basal respiration, net mineralisation, enzyme assays) in the examined soils.


Litter chemistry

As shown in Table 1, TOC and TP were similar in the acacia and spinifex litter, which were 40.2-41.8% and 0.44% respectively. TN in the acacia litter was 8-fold greater than that in the spinifex litter, resulting in a lower C: N ratio in the acacia litter (38) than the spinifex (268). [delta][sup.13]C values of the acacia and spinifex litters were -26.36%o and -14.12%c respectively, within the range of typical [C.sub.3] and [C.sub.4] plants.

Chemical composition of the acacia and spinifex litter based on characteristic peaks on the CP/MAS [sup.13]C-NMR spectra are showed in Fig. 1. Overall, in both acacia and spinifex litter, O-alkyl C (the sum of methoxyl, carbohydrate and di-O-alkyl C, 63.3-77.5%) was the highest among the C functional groups, followed by alkyl C (12.3-22.6%), aromatic C (the sum of aryl C and phenolic C, 7.7-8.0%) and carboxyl C (the sum of carboxylic, amide and ester C, 2.5-6.1%). No difference of the relative intensity of aromatic C in the litter was found between the two species, yet the former was characterised with higher intensities of alkyl C and carboxyl C, and lower intensity of Oalkyl C, compared with the latter.

Soil physicochemical properties

The soils beneath acacia and spinifex plants shared some similar basic properties (Table 2), such as WHC and C: N ratio. Other physicochemical properties appeared to be different in the soils beneath the two species, such as pH, TOC, TN and CEC. Specifically, pH in the acacia soil was lower than the spinifex. The levels of TOC, TN and CEC in the soils beneath acacia were 2-3 folds of those in the soils beneath spinifex. Labile fractions of TOC, WSOC, HWOC and Bioavailable OC were considerably higher in the acacia soil than the spinifex.


Microbial biomass, basal respiration, net mineralisation rate and enzymatic activities

Microbial biomass and activities in the surface soils were contrastingly different between acacia and spinifex (Table 3). MBC in the soils beneath acacia and spinifex were 219.2 and 104.3 mg [kg.sup.-1], respectively. Similar patterns were found for MBN, basal respiration rate and net mineralisation rate, which were 2-fold in the former compared with the latter.

Specific enzymatic activities related to litter decomposition and nutrient cycling in the soil were compared between the acacia and spinifex. Except for the neutral phosphatase, activities of dehydrogenase, invertase and urease activities were higher in the acacia soil than the spinifex soil. Specifically, the activities of dehydrogenase and invertase in the acacia soil were about twice as much as that in the spinifex and urease activity ~3-fold higher in the acacia soil than that in the spinifex soil.

Microbial profiles with PLFA biomarker

A general structure of soil microbial communities was reflected by PLFA biomarkers. In total, 27 PLFAs were identified in the analysis. The numbers of PLFAs (24-27) in soil underneath acacia and spinifex were within a similar range. Total PLFAs were higher in the acacia soil than the spinifex soil, which were 64.0 and 27.2 nmol [g.sup.-1], respectively (Table 4). In general, abundance of all the microbial groups of PLFAs was greater in the acacia soil than the spinifex soil.

The relative abundance of the individual PLFAs (mol %), as ratios of specific PLFAs to total PLFAs, suggested that bacteria is the most abundant (76.2-79.6%), followed by fungi (13.6-18.5%), AMF (3.5-4.4%) and actinomycetes (1.9-2.4%) in the soils colonised by the acacia and spinifex plants (Fig. 2). Although no differences were observed in the distribution of bacteria and actinomycetes (mol %) and G+: G--bacteria ratio in the soil between the two species, the relative abundance of AMF and fungi and the fungal: bacterial ratio were greater in the acacia soil than the spinifex (Fig. 2 and Table 4).

Interactions among plants, soil and microorganisms

The levels of TOC in the acacia soil were higher than the spinifex soil (Fig. 3). About half (58.5%) of TOC in the acacia soil was derived from [C.sub.3] plant, while 57.7% of TOC in the spinifex soil was derived from [C.sub.4] plant, indicating the dominant influence of in situ litters from each species on the soil TOC composition.

The RDA-environment ordination biplot showed specific associations between dominant site factors and individual PLFAs (Fig. 4). Several biotic and abiotic factors, including litter C: N ratio, pH, EC, CEC, WHC, TOC and its labile fractions were identified to be closely related to the soil microbial community composition. In particular, TOC and its labile fractions were positively related to the relative abundance of fungi and majority of G+ bacteria groups. The C: [N.sub.litter] ratio, EC and pH were positively associated with the relative abundance of AMF (16:1[omega]5c) and actinomycetes (10Me 18:0), but negatively associated with the abundance of fungi (18:2[omega]6,9c, 18:1[omega]9c, 18:1[omega]9t) and bacteria. The microbial groups were also closely related to the biochemical processes in the soils examined (Supplementary Materials fig. 1). Despite the relatively low abundance, AMF (16:1[omega]5c) and fungi (18:2[omega]6,9c, 18:1[omega]9c, 18:l[omega]9t) were positively correlated with the N cycle processes (net mineralisation and urease activities).




Native plant communities in arid landscapes are composed of native plant species colonising infertile landscapes, which are of low productivity and distributed in a patchy pattern, such as those under semiarid climatic conditions at Mt Isa (Reid and Hill 2013). From the present findings, nutrient (mainly N and P) status in the soils colonised by the native A. chisholmii and T. pungens plants was poor compared with those in productive crop/plantation soils (refer to Peverill et al. 1999). The nutrient supply, especially N supply, in the root zones seemed to rely on [N.sub.2]-fixing native acacia (A. chisholmii) and microbe-driven litter decomposition. Within the native plant community, surface soils underneath acacia and spinifex had been modified by in situ litter return, based on the [delta][sup.13]C values, in terms of TOC, structure and functions of microbial community, though it was unclear about the colonisation history of the two species at the sites sampled. The levels of MBC, MBN, basal respiration rate and net mineralisation rate in the acacia soil were about twice as much as those in the spinifex soil. Microbial communities in the acacia soil had a greater fungal:bacterial ratio than the spinifex soil. On this basis, the strategy for engineering growth media and root zones for revegetating native acacia-spinifex communities to cover mined lands at local base metal mines may be based on remediation options of plant organic matter to supply available nutrients and native acacia as host plants to rehabilitate native microbial communities for in situ litter decomposition and nutrient cycling, rather than nutrient-rich organic/inorganic fertilizer inputs. Biogeochemical properties in soil systems are closely coupled with the long-term development of the above ground plant communities. Modification of soil system properties induces changes of species diversity and abundance in the plant community through feedback mechanisms of in situ quantity and quality of plant litter and the abundance of functions of decomposer microbes in the rhizosphere (Wardle et al. 2004).

Importance of organic matter in infertile soil colonised by native plant species

The present soil (regardless of colonising plant species) contained much lower TOC compared with those reported in forest soils in semiarid area or those forest/pasture soils located in eastern Queensland with higher rainfalls than Mt Isa (Richards et al. 2007; Spain and Feuvre 1987; Xu et al. 2008). In general, TOC concentrations in the soil in this study were within similar ranges (2.7-16.6 g [kg.sup.-1]) of those found in the soils beneath natural shrub-grass plant community located in other semiarid regions (Shang and Tiessen 1998; Bird et al. 2002; Emmerich 2003; Bastida et al. 2006; Zhao et al. 2010). The annual input of plant litter was assumed to be low for both acacia and spinifex, due to water limitation for plant biomass production in semiarid regions (Facelli and Brock 2000). Even though detailed information about annual/seasonal patterns of plant litter inputs for both species was yet to be determined, it is assumed that higher litter inputs from the acacia stands might have occurred, compared with spinifex, based on the levels of TOC and TN. Soil organic matter is essential to the long-term soil fertility for sustainable plant biomass production (Tiessen et al. 1994), but its mineralisation rate and associated nutrient release in rate and composition should be in line with the ecophysiological requirements of target plant communities, due to the closely feedback between soil and plant systems (Wardle et al. 2004).


Nitrogen enrichment was also observed in the soil beneath acacia and spinifex with similar C: N ratio (13), much lower than those in the acacia litter (38) and spinifex litter (268). The majority of TOC in the examined soil was composed of microbial biomass or microbial by-products rather than the initial state of plant litter (Plaza et al. 2013). This might be the reason that the soil underneath both species have a similar C : N ratio, regardless of N concentrations of corresponding plants litter.

In natural ecosystems, plant litter and roots (not reported here) are the main sources of TOC, as shown by the isotope evidence of relative contribution of in situ plant litter and root inputs to TOC in the soil underneath the two plant species in the present study (Fig. 3). However, acacia species are generally short-lived (10-20 years) (Fox et al. 2001; also see and the presence of acacia stands at specific sites may also be impacted by bush fire (unfortunately without specific fire and ecology records available for the location). In our own field observations, we have also noticed the fact that new emergence of spinifex plants tended to concentrate around sites where old acacia plants have died off. This may be one of the reasons for the present patterns of [delta][sup.13]C values ([sup.13]C/[sup.12]C isotope ratios) in the surface soils which were influenced by the standing acacia and spinifex plants, rather than exclusively dominated by individual species at the sites sampled. Given the fact that litter decomposition rate in terrestrial ecosystems generally increases with initial litter N concentrations (Aerts 1997), higher N concentration in acacia litter than the spinifex may have enhanced the decomposition rate of acacia litter, contributing to enhanced nutrient cycling processes in the surface soils. This implies the importance of acacia species in local soil remediation either in the form of pioneer plants and/or plant mulch (organic matter) to engineer growth media with nutrient supply potentials in line with growth rates of native plant species to be revegetated across mined landscapes (including the >1000 ha tailings) at Mt Isa Mines.

Structure and functions of microbial community associated with acacia and spinifex species

Both soil and plant affect microbial community and associated biochemical processes (Buyer et al. 2002). Our assessment of structure and functions of microbial community was based on coarse PLFAs biomarkcrs in combination with enzyme assay evaluation. Although not allowing a very detailed characterisation of microbial community, it permits to understand the relationship between structure and functions of soil microbial community and in situ plant species. The number of PLFAs and relative distribution of major groups in microbial community in the root zone soil associated with both plant species were similar (Table 4), regardless of the different levels of microbial biomass and activities (Table 3). Overall, microbial community associated with both plant species were found to be highly bacteria dominant (>75%), especially G+ bacteria, which might be attributed to a high input of C from rhizodeposition of easily decomposable litter (e.g. sugar, carboxylic acid, amino acids) (Kuzyakov et al. 2007), promoting bacterial proliferation rather than fungal microorganisms (Buyer et al. 2002). A broad range of bacteria would be required to mediate soil biochemical processes such as C acquisition (DeAngelis et al. 2008), [N.sub.2] fixation (Evans and Ehleringer 1993), organic phosphorous mineralisation and dissolution (Rodriguez and Fraga 1999), contributing to overall organic matter decomposition and nutrient cycling processes (Supplementary Materials fig. 1).

The fungal:bacterial ratio is a widely used index to indicate the relative contribution of fungi and bacteria in soil microbial community. The values (0.14-0.25) in the present study, were within the similar range of grassland (0.19-0.22) (Breulmann et al. 2011), but lower than those reported in coniferous forest ecosystem (0.26-0.80) with relatively greater productivity under favourable fertility conditions (Frostegard and Baath 1996; Pennanen et al. 1999). Although AMF and total fungi biomass comprised only a minor proportion (<20%) of microbial communities in the examined soil, they are not only important to decomposition of more lignified organic compounds (e.g. lignin, phenol) (Araujo et al. 2012), but also play a vital role in improving plant growth through nutrient acquisition and tolerance resistance to drought (Michelsen and Rosendahl 1990), salts and metals (Ortega-Larrocea et al. 2010).

As a result, rehabilitation of microbial communities in engineered growth media would be critical to initiate and maintain litter decomposition and nutrient cycling for supporting the establishment and development of native acacia-spinifex communities revegetated across mined lands at Mt Isa region in the long-term. We have demonstrated the use of root zone soils from natural plant communities as carriers of native microbial communities in a parallel study to investigate factors and processes in biogeochemical rehabilitation of engineered technosols from weathered Cu-Pb-Zn tailings (Li et at. 2014, 2015).


In summary, the soils from native plant communities consisting of leguminous Acacia chisolmii and Spinifex grasses (Triodia spp.) were characterised by relatively low levels of soil organic carbon (6.03-14.17 g [kg.sup.-1]), microbial biomass (104.3-219.2 mg [kg.sup.-1]) and enzymatic activities, which have sustained the growth and recruitment of these native plant species in the infertile and dry landscapes of north-west Queensland. Surface soils underneath acacia and spinifex were also modified by in situ litter return, in terms of TOC, structure and functions of microbial community. Overall, the soil underneath Acacia chisholmii contained higher levels of TOC and N, microbial biomass, and enzymatic activities, with microbial communities of greater fungal:bacterial ratio, in comparison with those in soil underneath spinifex. This initial investigation has highlighted the greater contribution of native acacia species than spinifex in terms of organic matter, nutrient supply and fungi development. This has provided a general guidance for our further studies on remediation options for mine tailings rehabilitation.


Mount Isa Mines, Glencore Ltd (formerly Xstrata Copper Ltd) provided the tailings and soil samples and partial financial support to the analysis. We gratefully thank Prof. Rusong Wang, Prof. Dan Hu, Dr David Appleton, Dr Patrick Audet, Dr Ekaterina Strounina, Zulaa Dorjsuren, Chemistry Center (Department of Science, Information Technology and Innovation, Queensland Government), Analytical Center (School of Agriculture and Food Sciences, University of Queensland), State Key Laboratory of Urban and Regional Ecology (Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences) for technical assistance in the field and laboratory.


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Fang You (A), Ram C. Dalal (B,C), and Longbin Huang (A,D)

(A) University of Queensland, Centre for Mined Land Rehabilitation, Sustainable Mineral Institute, Brisbane, Qld 4072, Australia.

(B) University of Queensland, School of Agriculture and Food Sciences, Brisbane, Qld 4072, Australia.

(C) Department of Science, Information Technology and Innovation, Dutton Park, Qld 4102, Australia.

(D) Corresponding author. Email:
Table 1. Chemical properties of the acacia and spinifex litter

TOC, total organic carbon; TN, total nitrogen; TP, total phosphorous;
[delta][sup.13]C, the ratio of stable isotopes Carbon-13; Carbon-
12; Values are means (n = 3) with standard deviation in the
parenthesis; F and significant values were calculated in one-way

Parameters                              Acacia         Spinifex

TOC (%)                                40.2 (1.0)      41.8 (0.2)
TN (%)                                 1.05 (0.03)     0.16 (0.01)
TP (%)                                 0.44 (0.05)     0.44 (0.01)
C:N ratio                                38 (2)         268 (27)
[[delta].sup.13]C ([per thousand])   -26.36 (0.58)   -14.14 (0.02)

Parameters                              F       Sig.

TOC (%)                                 7.09    0.056
TN (%)                               2527.00    0.000
TP (%)                                  0.059   0.820
C:N ratio                             210.91    0.000
[[delta].sup.13]C ([per thousand])   1317.604   0.000

Table 2. Physicochemical properties in the soils beneath acacia and

WHC, water holding capacity; EC, electrical conductivity;
CEC, cation exchange capacity; Data are means of three replicates,
with standard errors in parentheses; WSOC, water soluble organic
carbon; HWOC, hot water extractable organic carbon; Bioavailable OC,
bioavailable organic carbon. Values are means (n = 3) with standard
deviation in the parenthesis; F and significant values were
calculated in one-way ANOVA

Parameters                             Acacia         Spinifex

WHC (%)                              32.2 (1.8)      27.9 (2.2)
pH                                    7.2 (0.0)       7.5 (0.0)
EC (mS [cm.sup.-1])                 0.052 (0.001)   0.071 (0.001)
CEC ([cmol.sub.c] [kg.sup.-1])       15.0 (3.6)       6.5 (0.8)
TOC (g [kg.sup.-1])                 14.17 (1.37)     6.03 (0.39)
TN (g [kg.sup.-1])                  1.1 1 (0.10)     0.47 (0.02)
  ([per thousand])                  21.29 (0.36)    19.31 (0.45)
C:N ratio                            12.8 (1.3)      12.7 (0.3)
TP (g [kg.sup.-1])                   0.45 (0.08)     0.43 (0.09)
Cu (mg [kg.sup.-1])                  94.3 (14.9)     93.1 (7.8)
Pb (mg [kg.sup.-1])                  18.0 (8.3)      22.1 (2.5)
Zn (mg [kg.sup.-1])                 371.4 (24.4)    295.5 (75.1)
WSOC (mg [kg.sup.-1])                17.8 (1.6)       8.6 (2.2)
HWOC (mg [kg.sup.-1])               205.1 (30.4)    114.2 (19.3)
Bioavailable OC (mg [kg.sup.-1])    768.0 (36.8)    436.0 (35.8)

Parameters                             F      Sig.

WHC (%)                               1.211   0.054
pH                                   60.500   0.001
EC (mS [cm.sup.-1])                 406.125   0.000
CEC ([cmol.sub.c] [kg.sup.-1])       15.814   0.016
TOC (g [kg.sup.-1])                  97.331   0.001
TN (g [kg.sup.-1])                  118.361   0.000
  ([per thousand])                   34.423   0.004
C:N ratio                             0.043   0.846
TP (g [kg.sup.-1])                    0.111   0.756
Cu (mg [kg.sup.-1])                   0.016   0.907
Pb (mg [kg.sup.-1])                   0.686   0.454
Zn (mg [kg.sup.-1])                   2.776   0.171
WSOC (mg [kg.sup.-1])                33.488   0.004
HWOC (mg [kg.sup.-1])                19.144   0.012
Bioavailable OC (mg [kg.sup.-1])    125.333   0.000

Table 3. Microbial biomass, basal respiration, and net mineralisation
rate, and enzymes including dehydrogenase, invertase, urease and
neutral phosphatase activities in the soils beneath acacia and

MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; TPF,
triphenylformazan; Values are means (n = 3) with standard deviation
in the parenthesis; F and significant values were calculated in one-

Microbial properties                        Acacia         Spinifex

MBC (mg [kg.sup.-1])                    219.2 (25.9)     104.3 (9.3)
MBN (mg [kg.sup.-1])                     36.4 (10.8)      17.2 (1.5)
Basal respiration rate                   27.4 (1.3)       16.8 (2.9)
  (mg C[O.sub.2]-C [kg.sup.-1]
Net mineralisation rate (mg Mineral       2.5 (0.2)        1.1 (0.0)
  N [kg.sup.-1] [day.sup.-1])

Enzymatic activities

Dehydrogenase ([micro]g TPF               37.2 (8.7)      15.1 (4.9)
  [g.sup.-1] [h.sup.-1])
Invertase ([micro]g glucose             1746.0 (216.4)   656.8 (180.3)
  [g.sup.-1] [h.sup.-1])
Urease ([micro]g N[H.sub.4]-N             51.2 (7.4)      14.2 (4.1)
  [g.sup.-1] [h.sup.-1])
Neutral phosphatase ([micro]g phenol      93.7 (4.4)      82.9 (7.3)
  [g.sup.-1] [h.sup.-1])

Microbial properties                       F      Sig.

MBC (mg [kg.sup.-1])                     52.439   0.002
MBN (mg [kg.sup.-1])                      9.446   0.037
Basal respiration rate                   33.617   0.004
  (mg C[O.sub.2]-C [kg.sup.-1]
Net mineralisation rate (mg Mineral     177.281   0.000
  N [kg.sup.-1] [day.sup.-1])

Enzymatic activities

Dehydrogenase ([micro]g TPF              14.582   0.019
  [g.sup.-1] [h.sup.-1])
Invertase ([micro]g glucose              44.846   0.003
  [g.sup.-1] [h.sup.-1])
Urease ([micro]g N[H.sub.4]-N            57.970   0.002
  [g.sup.-1] [h.sup.-1])
Neutral phosphatase ([micro]g phenol      4.850   0.092
  [g.sup.-1] [h.sup.-1])

Table 4. PLFA profiles of microbial community in the soils beneath
acacia and spinifex

PLFA, phospholipid-derived fatty acids; AMF, Arbuscular mycorrhiza
fungi; Bacteria G+, Gram-positive bacteria; Bacteria G-, Gram-
negative bacteria. Values are means (n = 3) with standard deviation
in the parenthesis; F and significant values were calculated in one-

PLFAs profile                             Acacia       Spinifex

Numbers of PLFAs                          27 (1)        24 (2)
Total PLFAs (nmol [g.sup.-1])           64.0 (9.7)    27.2 (6.1)
Actinomycetes PLFA (nmol [g.sup.-1])     1.2 (0.2)     0.7 (0.2)
AMF PLFA (nmol [g.sup.-1])               2.2 (0.3)     1.2 (0.4)
Bacteria PLFA (nmol [g.sup.-1])         48.8 (7.7)    21.4 (4.2)
Fungi PLFA (nmol [g.sup.-1])            11.8 (1.6)     3.8 (1.3)
Bacteria G+ PLFA (nmol [g.sup.-1])      24.8 (3.0)    11.6 (3.3)
Bacteria G PLFA (nmol [g.sup.-1])        6.0 (0.8)     3.0 (0.6)
Bacteria G+/G- ratio                     4.2 (1.0)     3.8 (0.4)
Fungal : Bacterial ratio                0.24 (0.01)   0.17 (0.03)

PLFAs profile                             F       Sig.

Numbers of PLFAs                         6.050    0.070
Total PLFAs (nmol [g.sup.-1])           30.759    0.005
Actinomycetes PLFA (nmol [g.sup.-1])     8.548    0.043
AMF PLFA (nmol [g.sup.-1])              11.685    0.027
Bacteria PLFA (nmol [g.sup.-1])         28.943    0.006
Fungi PLFA (nmol [g.sup.-1])            44.213    0.003
Bacteria G+ PLFA (nmol [g.sup.-1])      25.955    0.007
Bacteria G PLFA (nmol [g.sup.-1])       27.026    0.007
Bacteria G+/G- ratio                     0.395    0.564
Fungal : Bacterial ratio                12.358    0.025
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Article Details
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Author:You, Fang; Dalal, Ram C.; Huang, Longbin
Publication:Soil Research
Article Type:Report
Geographic Code:8AUST
Date:May 1, 2016
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