Soil ecology and agroecosystem studies - Microbial Ecology in Sustainable Agroecosystems - page 6

chemical controls on SOM (Waldrop et al., 2000; Balser and Firestone, 2005). Breakdown of
organic molecules is, for the most part, mediated by microbial enzymes, and if there are
barriers to the interaction of extracellular enzymes and substrate, decomposition is slowed
(Schimel and Weintraub, 2003; Allison, 2005; Ekschmitt et al., 2005). For over a century,
there has been interest in the nature of recalcitrant organic compounds in SOM. For an
extensive review of the controversial nature of “humic compounds” as artifacts of harsh
alkaline extractants, and more realistic alternatives to them, see the work of Kleber and
Johnson (2010).

1.2.2 The importance of litter quality and nutrients

Litter quality is defined in terms of the resistance of the material to decomposition.
Qualitative references to quality refer to materials that are readily decomposed with short
half-lives as being labile, while those that resist decomposition and possess longer half-
lives are termed resistant or recalcitrant. Early indices of quality relied on the ratios of C
and N or C and lignin. Under this convention, labile materials possess C:N ratios of less
than 30:1, while recalcitrant materials possess C:N ratios greater than 30:1. While useful,
these simple ratios have given way to more comprehensive approaches.
In both temperate and tropical ecosystems, chemically oriented indexes of litter (detri-
tus) quality have proven to be powerful predictive tools of rates of degradation and release
of nutrients. One of the more frequently employed ratios is the plant residue quality index
(PRQI; Tian et al., 1993, 1995). The PRQI builds on earlier indices by including C/N, lignin,
and polyphenol concentration of plant residues and is defined as

PRQI = [1/( a C/N + b lignin + c polyphenols)] × 100 (1.1)

where a , b , and c are coefficients of relative contribution of C/N ratio, lignin content (%), and
polyphenol content (%) to plant residue quality, respectively. Varying the relative contributions
of the three variables noted, such as varying the overall nutrient quality and quantity of crop
residues, is quite informative. With lower values of all three variables, there was a marked
mulching effect, leading to enhanced macrofaunal activities (e.g., increased termite and earth-
worm activity), allowing greater aeration and nutrient mineralization (Tian et al., 1995).
In tropical agricultural and agroforestry studies, a decision tree was created for testing
hypotheses about the resource quality parameters that affect nitrogen release patterns and
rates. The decision tree is linked to an Organic Resource Database (ORD) with detailed
information on the resource quality of several hundred species of leguminous crops and
agroforestry trees. This provides a systematic means of selecting organic resources for
soil fertility management (Palm et al., 2001). The chemical quality of an organic material
is influenced both by its carbon constituents (carbon quality) and by its nutrient content
and the chemical form of the nutrients (nutrient quality). Like the PQRI ( Equation 1.1 ) , this
approach includes a minimum set of resource quality characteristics for decomposition
studies (Palm et al., 2001), including lignin, soluble carbon, total nitrogen and phosphorus,
ash-free dry weight, and soluble phenolics if total nitrogen exceeds 1.8%. Measurement of
the protein-binding capacity to assess reactive polyphenols may be useful as well in some
instances. For an extensive overview of lignins and soils and major factors governing lig-
nin formation and decomposition, see the work of Thévenot et al. (2010).