Hydrologic-Carbon Cycle Linkages in a Subalpine Catchment

The feedbacks between the water and the carbon cycles are of critical importance to global carbon balances. Forests and forest soils in northern latitudes are important carbon pools because of their potential as sinks for atmospheric carbon. However there are significant unknowns related to the effects of hydrologic variability, mountainous terrain, and landscape heterogeneity in controlling soil carbon dioxide (CO2) efflux. Mountainous terrain imposes large spatial heterogeneity in the biophysical controls of soil CO2 production and efflux, including soil temperature, soil water content, vegetation, substrate, and soil physical properties. Strong spatial and temporal variability in biophysical controls can lead to large heterogeneity in the magnitude of soil CO2 efflux. This dissertation research investigates the relationships between these biophysical controls and the resultant CO2 efflux across the soil-atmosphere interface in a 393-ha subalpine catchment of the Northern Rocky Mountains. This study incorporates knowledge gained through field observations (2 growing seasons) at multiple locations distributed across the watershed, and a range of empirical analytical techniques including a modeling approach to estimate point to catchment scale soil CO2 efflux. Variability in soil CO2 efflux was strongly related to topography and landscape structure. Riparian meadows were found to have the highest rates of cumulative soil CO2 efflux across the entire watershed, likely due to more accumulation of soil water than upland sites, leading to enhanced plant and microbial respiration in riparian meadows. Landscape context and appreciation of organized heterogeneity are critical to estimation and interpretation of watershed-scale rates of soil CO2 efflux and for up-scaling plot or point measurements of soil CO2 efflux to larger spatial scales. This dissertation provides examples and suggestions for corroboration and integration of soil and canopy level CO2 fluxes and for process understanding of spatiotemporal variability of biogeochemical processes driven by the hydrologic cycle