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FIGURE 5.4. Hypothetical patterns of latitudinal variation in the contribution of the macro-, meso-, and microfauna to total soil fauna biomass. The effects on litter breakdown rates of changes in the relative importance of the three fauna size groups are represented as a gradient together with the faunal contribution to soil community metabolism. The favorability of the soil environment for microbial decomposition is represented by the cline of soil organic matter accumulation from the poles to the equator; soluble, or soil, organic matter (SOM) accumulation is promoted by low temperatures and waterlogging where microbial activity is impeded (from Swift et al., 1979).

FIGURE 5.4. Hypothetical patterns of latitudinal variation in the contribution of the macro-, meso-, and microfauna to total soil fauna biomass. The effects on litter breakdown rates of changes in the relative importance of the three fauna size groups are represented as a gradient together with the faunal contribution to soil community metabolism. The favorability of the soil environment for microbial decomposition is represented by the cline of soil organic matter accumulation from the poles to the equator; soluble, or soil, organic matter (SOM) accumulation is promoted by low temperatures and waterlogging where microbial activity is impeded (from Swift et al., 1979).

where X is the standing stock of litter and k is the annual fractional rate of disappearance. Olson (1963) proposed that it was a characteristic of mature forests that rates of litter production and disappearance were equal, so that annual production (L) would be balanced by breakdown (-kX). Olson used the symbol Xss to designate the standing stock of litter on the ground at steady state (i.e., when litter production and disappearance are equal). Then, the ratio of input (L) to standing stock (Xss) provides an estimate of breakdown rate k:

Olson (1963) estimated decomposition rates (k) for evergreen forests in various parts of the world (Fig. 5.5). Values for k ranged from 4 for rapid decomposition in tropical regions, through 0.25 for eastern United States pine forests, to 0.02 for higher latitude pine forests. Recent analyses using more sophisticated, mechanistic models have shown similar trends in litter decomposition across climatic gradients (e.g., Parton et al., 1989a; Moore and de Ruiter, 2000).

What is estimated here is the rate of leaf or needle litter breakdown. Olson's (1963), as most other models, did not consider inputs of organic litter belowground, although he did use the entire mass of carbon per square meters in estimates of Xss. Current studies of root dynamics (see Chapter 2) are providing estimates of root breakdown rates, but these are more difficult to measure than leaf litter breakdown rates and consequently are less well known. Root death and decay may account for as much as one-half of the annual carbon addition to soils in forests or even more in grasslands; but as is often the case, dynamics within the soil are obscure.

The simple exponential model using a single constant, k, to represent decomposition rate continues to be widely used. It is not difficult to estimate k using litterbag techniques (see next section of this chapter). The simple model loses its attractiveness when patterns of litter breakdown are examined more closely. Leaf litter often is a combination of leaf species, each with different breakdown rates. Furthermore, each species contains both labile and recalcitrant fractions. Wieder and Lang (1982) examined several different models, and concluded that the single exponential model shown previously or double exponential models (including fast and slow components) best describe breakdown rates over time "with an element of biological realism." Jenkinson et al. (1987) and Paustian et al. (1997) considered single-pool, multiple litter pool, and continuous spectrum models of litter decomposition, and provided mathematical representations of decomposition rates. Their results show that litter quality is a key factor for accurately modeling decomposition dynamics.

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