GRAZPLAN - DECISION-SUPPORT SYSTEMS FOR AUSTRALIAN GRAZING ENTERPRISES .3. PASTURE GROWTH AND SOIL-MOISTURE SUBMODELS, AND THE GRASSGRO DSS

This paper specifies the pasture growth module of a model for simulati ng grazing systems for ruminants ann the soil moisture budget that dri ves pasture growth. Both modules operate at a daily time step. The pas ture growth module is quite general in structure but recognises four f unctional groups of pasture plants: annual and perennial species are d istinguished, as are grasses and forbs. Shoot tissue is classified as live, senescing, standing dead, or litter, and also according to ifs d ry matter digestibility, thus enabling integration with diet selection and feed intake models. The phenological development of pasture plant s is modelled, with the transitions between each stage governed by env ironmental variables (day length, temperature and soil moisture). Prer eproductive and postreproductive pheno-stages of vernalisation and 'su mmer dormancy', respectively, are modelled in the appropriate cultivar s. Functions predicting net primary production in response to light in tercepted mean daytime temperature, and available soil moisture, and a lso the process of maturation, are common to all functional groups. Th e model's treatment of the allocation of assimilate has a similarly ge neral form. Seed and seedling dynamics are modelled for annual species only. GrassGro is a discrete computer package, developed for microsof t Windows(TM) that combines the pasture growth module with a module fo r predicting the intake of herbage of ruminants and their productivity , This decision support system enables users to analyse simplified gra zing systems in terms of pasture and animal production, gross margins, and year-to-year variability for any specified pasture cultivar, or c ombination of cultivars, at any specified site. The package may also b e used to simulate forward from current pasture and animal conditions, for assessing the probability distribution of production outcomes, gi ven the historical variability of weather conditions over the specifie d forward period. (C) 1997 Published by Elsevier Science Ltd.