A state-transition approach to understanding nonequilibrium plant community dynamics in Californian grasslands

Abstract

Usinga spatially and temporally replicated dataset, we built astate-transition model for Californian grasslands. We delineatedvegetation states by allowing TWINSPAN to classifyplot-level (≈10 m2) species cover datacollected over 3 to 5 consecutive years on 9 sites in an experimental designthat incorporated 5 residual dry matter (RDM) treatment levels representativeofthe range of grazing management prescriptions for this type (0, 280, 560, 841,1121 kg RDM·ha−1). We identified anddescribed a new California annual grassland subtype – Coast RangeGrassland – that is distinct from the previously described Coastal Prairieand Valley Grassland. Classification and regression tree(CART) analysis correctly classified 63% ofTWINSPAN-created vegetation transitions amongstates with interactions among site and monthly climate averages as the maindriving factors. The RDM variable (a surrogate for grazing intensity) wasimportant in model refinement, but only at a few site × year combinations andpredictions were rarely attributable to the grazing intensity gradient. Theequilibrium-based conclusion that grazing intensity manipulation createsdistinctive community structure was restricted in application to a few sites.The results suggest that equilibrium models may be appropriate for predictingsystem productivity but not the community composition, details of which requirea nonequilibrium approach. The nonequilibrium state-transition modeloffers considerable potential for improving the development and testing ofhypotheses about vegetation change and the limitations of management controls,but will require relatively large spatially and temporally replicated datasets.