Predicting and understanding the way natural communities change over time and recover from disturbance remains one of the great challenges to the field of ecology. Much of the research seeking to predict ecological community dynamics assumes that processes measured in intact communities can be used to predict the response to a disturbance. Preliminary results suggest that for the rocky shore seaweed community dominated by the red turf alga, this assumption does not hold true. This project combines empirical studies of variables that may have profound effects on the rate and trajectory of succession (species interactions, dispersal, life history characteristics and biogeographic region) with the predictive capabilities of modeling. Understanding the processes by which a disturbed area recovers is also a key to understanding the long-term consequences of human impacts to ecosystems. Such information can aid in the placement of reserves and other resource-use decisions. Having the ability to predict recovery rates based on empirical data will allow access to information that would otherwise be impossible to obtain without experimental disturbances. This research takes a multi-faceted approach to understanding intertidal community dynamics that will be useful information to coastal resource managers regarding recovery potential for intertidal organisms. This project also supports the thesis research of a doctoral student.
