The Sacramento-San Joaquin Delta in California was drained for agriculture and human settlement over a century ago, resulting in extreme rates of soil subsidence and release of CO2 to the atmosphere from peat oxidation. Because of this century-long ecosystem carbon imbalance where heterotrophic respiration exceeded net primary productivity, most of the land surface in the Delta is now up to 8 meters below sea level. To potentially reverse this trend of chronic carbon loss from Delta ecosystems, land managers have begun converting drained lands back to flooded ecosystems, but at the cost of increased production of CH4, a much more potent greenhouse gas than CO2.
To evaluate the impacts of inundation on the biosphere-atmophere exchange of CO2 and CH4 in the Delta, I first measured and analyzed net fluxes of CO2 and CH4 for two continuous years with the eddy covariance technique in a drained peatland pasture and a recently re-flooded rice paddy. This analysis demonstrated that the drained pasture was a consistent large source of CO2 and small source of CH4, whereas the rice paddy was a mild sink for CO2 and a mild source of CH4. However more importantly, this first analysis revealed nuanced complexities for measuring and interpreting patterns in CO2 and CH4 fluxes through time and space.
CO2 and CH4 fluxes are inextricably linked in flooded ecosystems, as plant carbon serves as the primary substrate for the production of CH4 and wetland plants also provide the primary transport pathway of CH4 flux to the atmosphere. At the spatially homogeneous rice paddy during the summer growing season, I investigated rapid temporal coupling between CO2 and CH4 fluxes. Through wavelet Granger-causality analysis, I demonstrated that daily fluctuations in growing season gross ecosystem productivity (photosynthesis) exert a stronger control than temperature on the diurnal pattern in CH4 flux from rice.
At a spatially heterogeneous restored wetland site, I analyzed the spatial coupling between net CO2 and CH4 fluxes by characterizing two-dimensional patterns of emergent vegetation within eddy covariance flux footprints. I combined net CO2 and CH4 fluxes from three eddy flux towers with high-resolution remote sensing imagery classified for emergent vegetation and an analytical 2-D flux footprint model to assess the impact of vegetation fractal pattern and abundance on the measured flux. Both emergent vegetation abundance and fractal complexity are important metrics for constraining variability within CO2 and CH4 flux in this complex landscape.
Scaling between carbon flux measurements at individual sites and regional scales depends on the connection to remote sensing metrics that can be broadly applied. In the final chapter of this dissertation, I analyzed a long term dataset of hyperspectral ground reflectance measurements collected within the flux tower footprints of three structurally similar yet functionally diverse ecosystems: an annual grassland, a degraded pepperweed pasture, and a rice paddy. The normalized difference vegetation index (NDVI) was highly correlated with landscape-scale photosynthesis across all sites, however this work also revealed new potential spectral indices with high correlation to both net and partitioned CO2 fluxes.
This analysis within this dissertation serves as a framework for considering the impacts of temporal and spatial heterogeneity on measured landscape-scale fluxes of CO2 and CH4. Scaling measurements through time and space is especially critical for interpreting fluxes of trace gases with a high degree of temporal heterogeneity, like CH4 and N2O, from landscapes that have a high degree of spatial heterogeneity, like wetlands. This work articulates a strong mechanistic connection between CO2 and CH4 fluxes in wetland ecosystems, and provides important management considerations for implementing and monitoring inundated land-use conversion as an effective carbon management strategy in the California Delta.
