Abandoned meander forest development patterns in a large alluvial southeastern floodplain, South Carolina, USA
Meitzen, Kimberly M.; Kupfer, John A.
Abandoned meanders are former river meanders cut-off from the active channel that occur in the floodplain in various stages of infilling. Their compositional diversity, ecological function, and persistence are highly variable in space and time. This study examines the spatial variability of vegetation dynamics, logging history, and hydrogeomorphic controls on abandoned meander forests in the Congaree River floodplain, South Carolina. The methods used for this study combine field-based vegetation (structure and composition) surveys with high-resolution digital terrain models, and 2D hydrodynamic modeling, soils data, and logging histories to explain spatial variability in forest patterns and hydrogeomorphic conditions. Annual duration and frequency of hydrologic connectiv ity to flood waters, topographic complexity, and logging history explained the greatest variability between sites. Un-logged old-growth forests were the most diverse, and differences in the canopy and understory demonstrated a long term process of species turnover indicative of changing hydrogeomorphic conditions from more hydric to less hydric as the abandoned channel continues to infill. Selective logging for Taxodium distichum (bald cypress) and clear cut logging created abrupt changes to community composition, whereby the recovering forests did not return to pre-disturbance assemblages. Landscape scale variability in hydrogeomorphic conditions and species biological tolerances controlled recruitment of the second-growth forests producing diverse structural and compositional patterns. The extent and intensity of logging impacts to T. distichum had not been previously documented, and its recovery within the floodplain is a major management concern particularly on account of current dam-related flow alterations. Floodplain forests dynamics of Eastern Coastal Plain river systems are ideal indicator sites for monitor ing and predicting ecosystem responses to natural and human-induced changes. Sustainable management of these forests are critical to their future health.