B31I-04:
Using Wavelets and Information Theory to Characterize the Direction, Strength, and Time Scale of Interaction between Environmental Drivers and Greenhouse Gas Exchange in Managed Wetlands of Northern California
Wednesday, 17 December 2014: 8:45 AM
Cove S Sturtevant1, Benjamin L Ruddell2, Sara H Knox1, Joseph G Verfaillie1, Jaclyn Hatala Matthes3, Patricia Y Oikawa1 and Dennis D Baldocchi1, (1)University of California Berkeley, Dept of Environmental Science, Policy, & Management, Berkeley, CA, United States, (2)Arizona State University, Fulton Schools of Engineering, Tempe, AZ, United States, (3)Boston University, Boston, MA, United States
Abstract:
Restoring agricultural areas to wetlands in the Sacramento-San Joaquin River Delta of California can help reverse subsidence and reduce greenhouse gas (GHG) emissions. Predicting outcomes and developing best practices of wetland management therefore requires a robust understanding of the sensitivity of GHG exchange in these ecosystems to factors such as management and meteorology. However, wetlands can exhibit complex, overlapping, and asynchronous couplings between site characteristics, environmental drivers and GHG exchange. In this research we demonstrate the use of wavelets and information theory (process networks) as sophisticated tools to disentangle and characterize ecosystem couplings to CO2 and CH4 exchange (measured by eddy covariance) in two restored Delta wetlands. Using wavelets we isolated processes acting at different time scales, then used process networks to determine the direction, strength, and lag properties of ecosystem couplings. We found that despite differences in age, architecture and management, CO2 exchange at both wetlands was most sensitive to similar meteorological factors such as radiation and temperature up to a time scale of several days. At the monthly timescale, however, the effect of a more variable water table management in one wetland became dominant, revealing a reduction in net CO2 uptake during long term water table drawdowns. The analysis of CH4 exchange in this wetland revealed a more sensitive and complex coupling with water table. CH4 exchange was sensitive to relatively small, multi-day shifts in water table and displayed a lagged response to larger, longer shifts. With these methods we were able to disentangle the effects of management from meteorology and better understand the sensitivities of GHG exchange. Our results provide important insights for modeling efforts and management practices.
