| Abstract: | The Wiegand and Milton (1996) simulation model predicts that vegetation dynamics in arid shrublands are characterized by event‐driven stochasticity (weather events), and demographic inertia (persistence of a species in a community) that lead to a lagged response in vegetation compositional change. Slow plant growth is one of the mechanisms driving slow vegetation change. We test this model at the same location (Tierberg Long‐term Ecological Research site) on which the model was based. Three dwarf shrub species, differing in palatability, were tracked over 25 years (1988–2014) at two levels of the past herbivory (pre‐1960) and three levels of the present herbivory (post‐1988). In the period between 1960 and 1988, all sites were grazed at the recommended agricultural stocking rate. For each species, plant density and a number of size attributes (basal diameter, height, canopy area) were surveyed. Analyses using a two‐way Analysis of Covariance (ANCOVA) took initial starting size into consideration. As the model predicted, event‐driven stochasticity (rainfall) resulted in an increase in density of the smaller size classes following a single large recruitment event across all grazing regimes for the palatable and unpalatable species. Size‐class distribution curve types remained unchanged illustrating that population demography remains unaffected for long periods and responses are slow (lagged response). Slow plant growth was evident in that there were no changes in height, canopy area, or density under present grazing regimes over the 25‐year period. Palatable species had a reduced canopy area and density compared to unpalatable species. Our findings provide empirical evidence supporting the predictions of the Wiegand and Milton (1996) model, notably event‐driven stochasticity, demographic inertia, and a lagged response in vegetation change in arid shrublands. In addition, our results support the model assumption of the significance of slow growth in long‐lived plant species and the influence of grazing regime. |
