Hardisky Rooted macrophytes are key mediators of methane efflux from wetland sediments to the atmosphere. Reduced carbon compounds released upon senescence of plant roots provide carbon substrates for a series of anoxic degradation's culminating in the production of methane within the sediment. Diffusion of methane into the apoplastic pathways within the plant, facilitate the movement of methane via aerenchyma tissues, through the plant and ultimately to the atmosphere. The critical boundary controlling both the release of carbon compounds to the sediment and diffusion of methane into the vascular plant is the root surface / sediment interface. This research will address the effects of various quantities and types of root biomass upon the efflux of methane from Typha marshes. To this end, we have proposed to plant natural mesocosms of Typha at four different densities and determine resulting differences in pore water methane and methane flux. The oxidizing/reducing nature of the edaphic environment is a second critical factor in controlling the rate of methane flux. We are proposing to investigate an existing hydrologic gradient where water table depth and Typha canopies vary from an open pool to the upland. Superimposed upon this gradient will be planned alterations in the water available to the marsh, creating the opportunity to investigate short term effects of water table fluctuations upon methane flux. Crucial to our understanding of the impacts of global climatic change is an ability to assess the impacts of change at the ecosystem level. Our most viable option for such study is through the use of remote sensing data. Our proposed research will relate canopy biophysical properties to canopy reflectance measures with ground-based instrumentation. We will in turn relate root biomass, pore water methane concentrations and methane flux to canopy reflectance. These ground-based models will then be used to quantitatively assess satellite (TM or XS) data and provide a methodolo gy capable of large area methane flux estimation.
