© 1997 Walt Dineen Society

Walt Dineen Society Annual Conference '97

Session VII: Marine Ecology Abstract #: 97708

Willsie, A.A.1, Fourqurean, J.W.1, Durako, M.D.2 and Zieman, J.C.3
1 Southeast Environmental Research Program and Department of Biology, Florida International University, Miami, Fl, 33199;
2 Florida Marine Research Institute, Florida Department of Environmental Protection, 100 8th Ave. SE, St. Petersburg, Fl 33701;
3 Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22903.


The purpose of seagrass monitoring in the Florida Keys National Marine Sanctuary (FKNMS) is to measure the status and trends of seagrass communities to evaluate progress toward protecting and restoring the marine resources of the Sanctuary. Specific objectives are: 1) To provide data needed to make unbiased, statistically rigorous statements about the status and temporal trends of seagrass communities in the Sanctuary as a whole and within defined strata; 2) To define reference conditions in order to develop resource-based water quality standards; and 3) To provide a framework for testing hypothesized pollutant fate/effect relationships through process-oriented research and monitoring. To reach these goals, four kinds of data are being collected in seagrass beds in the FKNMS: 1) Distribution and abundance of seagrasses using rapid assessment Braun-Blanquet surveys; 2) Demographics of the seagrass communities using leaf-scar counting and population demographics techniques; 3) Seagrass productivity of the dominant species of seagrass (Thalassia testudinum) using the leaf-mark and harvest method; and 4) Seagrass nutrient availability using tissue concentration assays. We assess both inter-annual and intra-annual trends in seagrass communities. The mix of site types is intended to monitor trends through quarterly sampling at a few permanent locations and to annually characterize the broader seagrass population through less intensive, one-time sampling at more locations. Clear spatial and seasonal patterns in productivity, demographics, distribution, abundance, and elemental content are present in the data.


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