Introduction

Biologically and biochemically mediated processes in soils are fundamental to terrestrial ecosystem function. Members of all trophic levels in ecosystems depend on the soil as a source of nutrients and depend on soil organisms to release and recycle key nutrient elements by decomposing organic residues. These biotic decomposition processes are studied at three levels of resolution (Sinsabaugh et al., 2002). At the molecular level, plant fiber structure and enzymatic characteristics of degradation are investigated. At the organismal level, the focus is on functional gene analyses, regulation of enzyme expression, and growth kinetics, whereas at

TABLE 3.1 Books and Book Chapters of Methods in Soil Microbiology

Methods in soil microbiology

References

Gross nitrogen fluxes (15N pool dilution) Soil biological processes and soil organisms

Soil microbiology and soil biochemistry

Fungi

Actinomycetes

Digital analysis of soil microorganisms Soil enzymes

Tracer techniques (13C, 14C, 11C, 15N)

Alef and Nannipieri (1995), Schinner et al. (1996),

Levin et al. (1992), Weaver et al. (1994) Frankland et al. (1991), Newell and Fallon (1991) McCarthy and Williams (1991) Wilkinson and Schut (1998) Burns and Dick (2002)

Schimel (1993), Boutton and Yamasaki (1996), Coleman and Fry (1991), Knowles and Blackburn (1993) Murphy et al. (2003) Robertson et al. (1999)

the community level, research concentrates on metabolism, microbial succession, and competition between microbial and faunal communities. These three levels must be integrated to fully understand microbial functions in soils (Sinsabaugh et al., 2002). The function of soil biota is investigated by a range of methods focusing either on broad physiological properties (e.g., soil respiration, N-mineralization) or on specific enzymatic reactions carried out by soil microorganisms (e.g., ammonia monooxygenase of nitrifiers). The activity of approximately 100 enzymes has been identified in soils (Tabatabai and Dick, 2002). A challenge for the future is to localize these enzymes in soils and relate their activity to soil processes at higher levels of resolution.

This chapter focuses primarily on the more important biochemical and physiological methods applied in soil microbiology and soil biochemistry today. Biochemical techniques are used to determine the distribution and diversity of soil microorganisms, whereas physiological methods are used to understand the physiology of single cells, the activity of soil microbial communities, and biogeochem-ical cycling at the ecosystem level. Faunal abundance and activity are discussed in Chap. 7. Table 3.1 provides references for more detailed studies of biochemical and physiological methods used to study soil microorganisms.

Before starting any analysis in soil microbiology, it is important to select an adequate experimental design and sampling strategy. Pico- and nanoscale investigations are used to reveal the structure and chemical composition of organic substances and microorganisms as well as to investigate the interactions between the biota and humic substances. These fine-scale approaches can identify organisms, scale of investigations and collection of samples

TABLE 3.2 Physical, Chemical, and Biological Properties That Help to Interpret Data on the Function and Abundance of Soil Biota

Physical and chemical soil properties

Biological soil properties

Topography

Particle size and type

Plant cover and productivity

Parent material

CO2 and O2 status

Vegetation history

Soil type, soil pH

Bulk density

Abundance of soil animals

Moisture status

Temperature: range and variation

Microbial biomass

Water infiltration

Rainfall: amount and distribution

Organic matter inputs and roots present

unravel their relationships, determine their numbers, and be used to measure the rates of physiological processes. Such results boost our understanding of chemical and biological processes and structures at larger scales. Microscale investigations concentrate either on soil aggregates or on microhabitats characterized by high turnover of organic materials (e.g., the rhizosphere, drilosphere, and soil-litter interface). High-activity areas are heterogeneously distributed within the soil matrix. Hot spots of activity may make up less than 10% of the total soil volume, yet may represent more than 90% of the total biological activity (Beare et al., 1995). Up-scaling data from the microscale to the plot or regional scale remains difficult because spatial distribution patterns are still largely unknown.

Sampling at the plot scale is the most common strategy used for soil chemical and biological studies. A representative number of soil samples is taken from the study site and either combined to make a composite sample or treated as individual, spatially explicit samples. Typically, a series of random samples is taken across representative areas that are described by uniform soil type, soil texture, and habitat characteristics. Samples of agricultural soils are often taken from specific soil depths (e.g., 0-20 or 0-30 cm); samples of forest soils are taken from specific soil horizons (e.g., litter horizon, A horizon). Descriptions of sampling time, frequency, and intensity as well as preparation, archiving, and quality control are given by Robertson et al. (1999). Soil microbiological data obtained from soil samples become more informative if supplemented by information on the soil physical, chemical, and biotic factors (Table 3.2).

Approaches to sampling must take into account spatial distribution of the soil biota, which depends highly on the organisms studied and the characteristics of the study area (Table 3.3). When topography and soil chemical and physical properties are relatively uniform, spatial patterns of soil biota are structured primarily by plants (plant size, growth form, and spacing). Therefore, simple a priori sampling designs are often inappropriate. A nested spatial sampling design is useful to explore spatial aggregation among a range of scales. For patch size estimation and mapping at a particular scale, the spatial sampling design can be optimized using simulations. To increase the statistical power for hypothesis testing in belowground field experiments and monitoring programs, exploratory spatial sampling and

TABLE 3.3 The Relationship of Soil Microbial Properties to Sampling Scale, Taxonomic Resolution, and Ecosystem"
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