OOS 20-4 - Climate extremes drive changes in functional community structure

Wednesday, August 10, 2016: 9:00 AM
Grand Floridian Blrm H, Ft Lauderdale Convention Center
Jennifer S. Rehage, Earth and Environment, Florida International University, Miami, FL and Ross E. Boucek, Biology, Florida International University, Miami, FL
Background/Question/Methods

The response of communities to climate extremes can be quite variable. Much of this variation has been attributed to differences in community-specific functional trait diversity, as well as community composition. Yet, few if any studies have explicitly tested the response of the functional trait structure of communities following climate extremes (CEs). Recently in South Florida, two independent, but sequential potential CEs took place, a 2010 cold front, followed by a 2011 drought, both of which had profound impacts on a subtropical estuarine fish community. These CEs provided an opportunity to test whether the structure of South Florida fish communities following each extreme was a result of species-specific differences in functional traits.

Results/Conclusions

From historical temperature (1927–2012) and freshwater inflows records into the estuary (1955–2012), we determined that the cold front was a statistically extreme disturbance, while the drought was not, but rather a decadal rare disturbance. The two disturbances predictably affected different parts of functional community structure and thus different component species. The cold front virtually eliminated tropical species, including large-bodied snook, mojarra species, nonnative cichlids, and striped mullet, while having little affect on temperate fishes. Likewise, the drought severely impacted freshwater fishes including Florida gar, bowfin, and two centrarchids, with little effect on euryhaline species. Our findings illustrate the ability of this approach to predict and detect both the filtering effects of different types of disturbances and the implications of the resulting changes in community structure. Further, we highlight the value of this approach to developing predictive frameworks for better understanding community responses to global change.