Tropical Grasslands (1994) Volume 28, 229–240

State and transition models for rangelands.
5. The use of state and transition models for predicting vegetation change in rangelands

J.C. SCANLAN

Land Protection Branch, Department of Lands, Brisbane, Queensland, Australia

Abstract

State and transition models are similar in nature to Markov models which have been applied in the field of ecology since the 1960s. Variations to true Markov processes that have been used in ecology include second-order, discrete Markov and semi-Markov processes and continuous-time Markov processes.
The uses of discrete-time and continuous-time Markov models are discussed. Three examples of how vegetation dynamics can be simulated by Markov models are presented. The way in which altered climate may alter the course of vegetation change is described for Prosopis savanna in south Texas (USA). Chemical control strategies for Acacia nilotica management in north-western Queensland were compared by incorporating a Markov model into a simulation model which included the effect of woody vegetation on pasture growth, as well as prediction of liveweight gain of cattle. The impact of altering grazing pressure on pasture composition change is presented using a continuous-time Markov model of pastures in tropical woodlands of northern Australia.
These examples indicate how state and transition models can be used. State and transition models may be used for prediction and analysis in addition to aiding communication. The integration of Markov models into process models shows promise for devising complex management models for rangelands.

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