FCE LTER Journal Articles
Hydrological drivers of wetland vegetation community distribution within Everglades National Park, Florida
Abstract
The influence of hydrological dynamics on vegetation distribution and the structuring of wetland environments is of growing interest as wetlands are modified by human action and the increasing threat from climate change. Hydrological properties have long been considered a driving force in structuring wetland communities. We link hydrological dynamics with vegetation distribution across Everglades National Park (ENP) using two publicly available datasets to study the probability structure of the frequency, duration, and depth of inundation events along with their relationship to vegetation distribution. This study is among the first to show hydrologic structuring of vegetation communities at wide spatial and temporal scales, as results indicate that the percentage of time a location is inundated and its mean depth are the principal structuring variables to which individual communities respond. For example, sawgrass, the most abundant vegetation type within the ENP, is found across a wide range of time inundated percentages and mean depths. Meanwhile, other communities like pine savanna or red mangrove scrub are more restricted in their distribution and found disproportionately at particular depths and inundations. These results, along with the probabilistic structure of hydropatterns, potentially allow for the evaluation of climate change impacts on wetland vegetation community structure and distribution.
Recommended Citation
Todd, M.J., R. Muneepeerakul, D. Pumo, S. Azaele, F. Miralles-Wilhelm, A. Rinaldo, I. Rodriguez-Iturbe. 2010. Hydrological drivers of wetland vegetation community distribution within Everglades National Park, Florida. Advances in Water Resources 33(10): 1279-1289.
Comments
This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.