Modeling Effects of Spatial Pattern, Drought, and Grazing on Rates of Rangeland Degradation: A Combined Markov and Cellular Automaton Approach

The hybrid Markov-cellular automaton model simulates vegetation dynamics as a spatially and temporally discrete system. Temporal dynamics are controlled by the transition probabilities among these states, whereas spatial dynamics are controlled by local rules determined either by neighborhood configuration or by its association with the transition probabilities. In this chapter, the authors present an M-CA model of interactions between spatial patterning of vegetation, drought, and cattle grazing in a landscape context. The effects of drought, grazing, and spatial pattern can be thought of as operating at different scales: drought at large (regional) scales, grazing at intermediate (landscape) scales, and spatial pattern at small (patch) scales. Drought and grazing affect vegetation dynamics externally by differentially affecting the two functional groups of plants.

Duke Scholars

Author James F. Reynolds Environmental Sciences and Policy