Variations in Penman-Monteith derived bulk surface conductance of boreal aspen and black spruce forests

Boreal forest accounts for 30% of the Canadian landscape and plays an important role in the global carbon and water cycles. How these processes will change with respect to climatic variability is poorly understood. Our goal is to improve our understanding of the integrated system response (climate, hydrology, soil and vegetation) of the southern boreal forest to variation in climate. Continuous measurements have been made since 1996 at Old Aspen and 1999 at Old Black Spruce as part of Boreal Ecosystem Research and Monitoring Sites (BERMS) and Fluxnet Canada/Canadian Carbon Program. In addition to climate variables, we have high-quality year-round EC measurements of evapotranspiration (E), and related micrometeorological fluxes of momentum, sensible heat, and CO2. We carry out QA/QC, archive and gap fill these data, and synthesize the results to determine trends in climate and fluxes. Over the measuring period, E at Old Aspen has ranged from 264 mm y-1 to 450 mm y-1 while at Old Black Spruce less variation has been seen with a range of 271 mm y-1 to 331 mm y-1. Lower average E at Old Black Spruce even with slightly lower precipitation has resulted in a significantly higher contribution to groundwater (i.e., precipitation (P) - E). It was 33% higher on average over the 10 years after the drought in 2001-2003. During the drought years the difference was much larger with mostly negative P - E values at Old Aspen.

As part of research to improve models of forest E, data analysis is under way to determine a Penman-Monteith derived time series of bulk surface conductance. Variations in the conductance are evaluated through comparisons of periods selected for dry and wet canopy conditions and differences between the coniferous and deciduous ecosystems. Main controlling variables on the conductance, such as PAR, VPD, soil moisture and LAI, are being identified in order to increase the spatial domain of application. The relationship between the control variables and conductance is monitored for changes over the long term, including drought and wet periods. This research will help supplement work needed to improve parameterization of hydrologic processes in land surface models such as CTEM and CLASS.