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The most commonly used parameters for assessing soil microbial activity are described in the following.

34 1.3.2.1 The microbial biomass carbon (Cmic)

The quantitative measurement of microbial biomass carbon (Cmic) is expressed as

µg g-1 of dry soil (Anderson and Domsch, 1978; Jenkinson et al., 1981; Jenkinson, 1988; Sequi, 2000).

1.3.2.2 The ratio of microbial biomass carbon to total soil organic carbon (Cmic/Corg)

This ratio expresses the amount of microbial biomass carbon within the pool of soil organic carbon. Several authors put forward the hypothesis that soils that exhibit a level of bioactivity per unit Corg higher than an empirical average are "developing" soils

with a net accumulation of organic carbon, and those with a lower level belong to more stable systems (in equilibrium) and are losing organic carbon from a pool of relatively stable humic materials. That is, small amounts of Cmic within a large pool of Corg are

likely to mean that the average availability (but not the actual amount) of the carbon source must be low, due to the very stable quality of the soil organic matter, hardly attackable by the microflora (Insam & Domsch, 1988).

Experiments studying the chronosequence of reforested soils showed a decrease of the Cmic/Corg ratio over time, thus meaning that the availability of carbon decreased in

the target horizon at the expenses of the microbial community, as the ecosystem was moving toward steady state (Sequi et al., 2000; Jenkinson et al., 2004). After a three- years extensive survey of 134 plots located in 26 different sites, Anderson and Domsch (1989) found that, regardless the soil tipology, the Cmic/Corg ratio was significantly

higher in plots under continuous crop rotation than in plots with a long history of monoculture (expressed as percentages, 2.9% vs. 2.3%, respectively): the authors therefore considered the crop rotation system as taking a less advanced position in the ecological succession to steady state with respect to the monoculture one. However, when organically fertilised by green manuring, both the systems exhibited equal values of the Cmic/Corg ratio, just one year after the amendment, meaning that the microbes soil

population became capable to suddenly grow thanks to a sort of "priming effect", probably caused by the high amount of easily decomposable organic matter in the rizhosphere and detritusphere (Kuzyakov, 2010).

35 1.3.2.3 The microbial respiration

The microbial basal respiration is function of the soil organic matter decomposition by the microorganisms and it is expressed as mg C-CO2 kg-1 dry soil.

Another version is represented by the substrate-induced microbial respiration - SIR (mg C-CO2 kg-1 dry soil) consisting in the addition of a certain amount of glucose to the soil

sample to stimulate microbial respiration. Moreover, the microbial respiration rate is also utilized, given by the C-CO2 released by the soil over a certain time t: by measuring the rate it is possible to graphically depict the respiration curves, obtained from both cumulative and daily measurements (Anderson and Domsch, 1978; Anderson and Domsch, 1993; Sequi et al., 2000; Bloem et al., 2006).

1.3.2.4 The metabolic quotient (qCO2)

The metabolic quotient (qCO2), also known as specific respiration rate, represents

the ratio of respiration to microbial biomass: this index actually describes the substrate mineralized per unit of microbial biomass carbon (Anderson and Domsch, 1993). The metabolic quotient is conceptually based on Odum's theory of ecosystem succession (1969), that is, a low value of the quotient would indicate a more efficient use of the energy thus reflecting a more stable (mature) ecosystem (Insam and Haselwandter,

1989; Anderson, 1994); higher values of qCO2 would instead denote situations of

disturbance or youthful traits of the ecosystem (Anderson and Domsch, 1985). Higher

qCO2 of microbial communities from young sites have been observed compared to

matured sites (Insam and Domsch, 1988).

In addition, this ratio has been widely used as a good indicator of the alterations that take place in soil due to heavy metal contamination (Brookes, 1995; Liao and Xiao, 2007), deforestation (Bastida et al., 2006a), temperature (Joergensen et al., 1990) or changes in soil management practices (Dilly et al., 2003).

However, the index has also been criticised for its incapacity to distinguish between an actual ecosystem development process from microbial stress/ external disturbance: e.g. low pH and/or low nutrients availability are likely to keep low the microbial biomass thereby causing a high qCO2, even in a mature ecosystem; likewise,

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negatively) merely because microbial respiration/biomass are temporarily affected too (Wardle and Ghani, 1995).

Wang et al. (2003) studied the relationships among soil respiration, microbial biomass, clay content and substrate availability and argued that the latter, instead of the size of microbial biomass, was the principal determinant to soil respiration under favourable temperature and moisture conditions: according to the measurements, the variations in soil respiration could be presumably attributed to the changes in the chemistry of soil organic matter. Given these findings, the authors concluded that relationships of soil respiration and organic C turnover to the size of microbial biomass remained unclear.

1.3.2.5 Other indicators

There are other analyses that can be used to assess soil microbial activity. These can include various other methods of biomass appraisal and estimates of nutrient cycling (Sequi, 2000; Bloem et al., 2006). Microbial activity can be assessed in a number of ways that indicate the status of either the total community or in some cases specific members of that community. Individual strains can be studied to determine fluctuations in population or activity with perturbation. For example, specific pathogens may be an important indicator of soil quality in some systems (Ritz et al., 1994; Sequi, 2000; Bloem et al., 2006). Nitrifier populations, besides being a key group in the nitrogen cycle, are very sensitive to environmental stress and therefore may be a group of interest in soil quality assessment (Bock et al., 1989).

Enzyme assays may provide information on the microbial activity in soil (Dick, 1994; Bandick and Dick, 1999). Dehydrogenase, phosphatase, arginine and arlysulfatase are just examples of useful enzymes that can be utilised (Badiane et al., 2001). Lagomarsino et al. (2009), in an experiment comparing organic vs. conventional management in a Mediterranean environment, observed a general increase of hydrolytic enzymes activities in soil under organic management. The authors identified the β- glocosidase as a suitable indicator to predict organic C accumulation in soil.

Fatty acid profiles are characteristic of specific genera and species (DeBoer and Sasser, 1986) and may play a role in assessing the soil microbial community (Zelles, 1999).

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The heterogeneity of the DNA recovered from soil is a reflection of community diversity (Torsvik et al., 1990; Faoro et al., 2010). DNA/RNA fingerprints may be intrinsically representative of the microbial community of a given soil (Holben et al. 1988; Asbhy et al., 2007).

Soil microorganisms may also be characterized on the basis of their functional diversity, namely their specific metabolic fingerprint: patended methods as the "BIOLOG Plates technique" allow to identify, in a very simple way, more than 1,500 different species of fungi and bacteria.

1.3.3 Interactions between the soil microbial community and the organic matter