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Utilizing a historical database to refine ground cover vegetation as indicators of wetland hydrology
Authors:Paul E Thurman  Thomas L Crisman  David Carr
Institution:1.Department of Integrative Biology,University of South Florida,Tampa,USA;2.Southwest Florida Water Management District,Brooksville,USA
Abstract:Indicator species provide an easy and quick method of evaluating ecosystems. The species comprising the most useful indicators of wetlands should be distributed across a range of water depths and inundation durations, while each species is representative of a specific condition. Hydrophytic vegetation is commonly used to determine the existence and type of wetland; however, such indicator systems often depend on assigning species qualitatively to discrete categories based on assumptions about their distribution along a gradient of conditions. The current study proposes a wetland indicator system based on the quantitative responses of individual vegetation species to a gradient of water depths and periods of inundation. A long-term database was utilized to determine species responses to hydrological alterations in a series of wetlands. The hydrophytic plant species investigated (n = 29) displayed relatively narrow ranges of mean hydrologic values and were distributed linearly along multiple hydrologic gradients (hydroperiod, average water depth, and maximum water depth) ranging from Amphicarpum muhlenbergianum which was observed at the shallowest water depths and shortest hydroperiod to Pontederia cordata and Ludwigia repens which were characteristic of wetlands with the deepest water and longest hydroperiod. The species distribution and means along the hydrologic gradients tested indicates they are prime candidates for inclusion in a quantitative or continuum indicator system. The historical database utilized for this study provided valuable information for numerous species common to the Tampa Bay region for which little or no ecological information was previously available. The methodology utilized in this paper provides a cost and time effective method for obtaining the vast amounts of information required to refine plant indicator systems using a large number of species.
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