The Value of Modeling Botanical Composition Change in Grasslands

The integration of grassland dynamics, livestock production and economics is necessary to improve decision making regarding grassland resource development and management. Within a sward, the relative competitive ability of different species and the way management interacts with the environment both play a significant role in determining the competition between species, future states of the grassland sward, ecological impact of the grassland and its potential for livestock production (Kemp and King, 2001). The impact of botanical composition shifts on grassland productivity will depend on the nutritive value and yield potential of the invasive species against those of the resident species. The seasonality and spatial distribution of forage and its quality will influence selective grazing, livestock productivity and potential profitability from the grassland. Long-term grazing trials in Australia have described how the persistence of different species interacts with management and climate to determine the resilience of a pasture system. Most large changes in grassland populations are episodic and coincide with either favourable growing conditions or periods of stress, especially under conditions of overgrazing and drought. Annual cycles in botanical composition are a continually dynamic seasonal process that over the long term may reflect the dominance of a particular functional group of species (Kemp and King, 2001). It has been suggested that the state and transition model proposed by Westoby et al. (1989), adequately represents Australian grasslands. The modelling of functional groups, in terms of their seasonality of growth, responses to drought and grazing, capacity for livestock production and environmental value, would enhance the applicability of the state and transition model to grassland resource and management decision making systems in broadly different environments. This is supported by previous work where ordination of grassland survey data showed similar group interactions and relative changes define the variable states of grasslands and transitions between states in response to both management and climate (Westoby et al., 1989; Kemp and King, 2001). Modelling functional groups also allows incorporation of desirable native or naturalized species that fit into sown species functional groups, as some native species in Australian grasslands make significant contributions to grassland productivity, sustainability and profitability. The objective of this study is to determine the value of modelling botanical composition changes in grasslands under both stochastic and deterministic climatic conditions. This value is measured through its simulated effects on both biophysical and economic outcomes