Challenges in using siliceous subfossils as a tool for inferring past water level and hydroperiod in Everglades marshes

Successfully rehabilitating drained wetlands through hydrologic restoration is dependent on defining restoration targets, a process that is informed by pre-drainage conditions, as well as understanding linkages between hydrology and ecosystem structure. Paleoecological records can inform restoration goals by revealing long-term patterns of change, but are dependent on preservation of biomarkers that provide meaningful interpretations of environmental change. In the Florida Everglades, paleohydrological hind-casting could improve restoration forecasting, but frequent drying of marsh soils leads to poor preservation of many biomarkers. To determine the effectiveness of employing siliceous subfossils in paleohydrological reconstructions, we examined diatoms, plant and sponge silico-sclerids from three soil cores in the central Everglades marshes. Subfossil quality varied among cores, but the abundance of recognizable specimens was sufficient to infer 1,000–3,000 years of hydrologic change at decadal to centennial resolution. Phytolith morphotypes were linked to key marsh plant species to indirectly measure fluctuations in water depth. A modern dataset was used to derive diatom-based inferences of water depth and hydroperiod (R2 = 0.63, 0.47; RMSE = 14 cm, 120 days, respectively). Changes in subfossil quality and abundances at centennial time-scales were associated with mid-Holocene climate events including the Little Ice Age and Medieval Warm Period, while decadal-scale fluctuations in assemblage structure during the twentieth century suggested co-regulation of hydrology by cyclical climate drivers (particularly the Atlantic Multidecadal Oscillation) and water management changes. The successful reconstructions based on siliceous subfossils shown here at a coarse temporal scale (i.e., decadal to centennial) advocate for their application in more highly resolved (i.e., subdecadal) records, which should improve the ability of water managers to target the quantity and variability of water flows appropriate for hydrologic restoration.