In the Gulf of Mexico, barrier islands absorb the majority of the wind and wave action from storms, resulting in modification of dune morphology and vegetation dynamics. Understanding changes in dune vegetation in response to storms can identify the ecological processes occurring in these areas as well as help predict future effects of tropical storms. Since 1999, T. Miller of Florida State University has been collecting data describing the dynamics of dune vegetation on St. George Island. These long-term census data provide an opportunity to investigate the ecology of dune ecosystems.
I analyzed this ten-year data set to quantify how vegetation responds to major storms and determine which dune species would be most useful for restoring damaged coastal areas. This approach was tested using six plant species that were identified by T. Miller as particularly robust to the effects of storms. I conducted a transplant experiment with these six species across dune microhabitats and quantified transplant survival and growth over time in each habitat. Results suggest that, while several of these species have significant potential for restoration use, the habitat from which a transplant species originates is not a good indicator of its success in different habitats. Further, it appears that transplants encourage succession on degraded habitat. I explored the potential to extrapolate this restoration technique to a broader group of landscapes using GIS and aerial images to characterize vegetation change over time on St. George Island and compared these data with long-term census data. Additionally, I investigated if remote sensing could be used to identify locations that were similar to St. George in the distribution of dune habitats and the effects of storms across these areas. Results suggest that remote sensing approaches can be useful for a subset of habitat and species types on barrier islands.
Lastly, I used estimates of plant growth in good and bad years from the long-term data to build a model that describes succession in dune habitats. The model can be used to identify how dune communities might respond to a change in storm frequency. The model predicts that an increasing frequency of storms will result in plant species turnover in each dune community with the foredune community expressing the most dramatic changes.
