The model comprises three submodels, which together give an integrated picture of nitrogen pools and fluxes in grassland under grazing or cutting. The first submodel represents the interaction of the grazing animal with the sward through intake and the production of excreta; the second is concerned with the growth of the vegetative grass crop and its response to light, temperature and nitrogen; these two submodels are interfaced with a submodel of soil earbon and nitrogen pools and processes, including dead shoot and root material, dead and live soil organic matter, and three pools representing mineral nitrogen. No account is taken of water, whieh is assumed to be non-litniting, or the possible effects of soil pH and soil aeration. The niodel is used to simulate a range of tnatiagetnent strategies as applied to stocking density and fertilizer application, examining both steady-state and nonsteady-state conditions. The model highlights the long time scales associated with grassland systems, the role of the grazing animal in modifying carbon and nitrogen flows, and the importanee of soil conditions to grassland productivity and fertilizer response. The productivity of grazed swards may be greater or less than that of cut swards dependitig oti stocking density and fertilizer application, although nitrogen reeovery (as calculated here) is always lower in grazed swards. The model is able to stitnulate mineralization and immobilization, and place these in the context of plant processes atid the grazing atiimal.

A mathematical model was developed to describe carbon (C) and nitrogen (N) cycling in different soil types, e.g. clay and sandy soils. Transformation rates were described by first-order kinetics. Soil organic matter is divided into four fractions (including microbial biomass pool) and three fractions of residues. The fraction of active soil organic matter was assumed to be affected by the extent of physical protection within the soil, as was the soil microbial biomass. The extent of protection influenced the steady state level of the model, and, hence, the mineralization rates. The mineralization rate in fine-textured soils is lower than in coarse-textured soils; in fine-textured soils a larger proportion of the soil organic matter may be physically protected. The availability of organic materials as a substrate for microorganisms is not only determined by their chemical composition, but also by their spatial distribution in the soil. (Abstract retrieved from CAB Abstracts by CABI’s permission)

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