Scaling the Physiology and Structure of Forests in Space and Time

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This research will address the role of forest physiological processes and forest structural characteristics in the terrestrial carbon (C) cycle. The research will leverage much of the existing equipment and data that we have obtained over the last decade. The research program has three components: (a) a field measurement component; (b) an ecophysiological modeling component and (c) an airborne and satellite remote sensing component. The combination of these approaches will permit us to maintain a highly innovative research environment for the continued training of graduate students and other highly-qualified personnel. The research program has three objectives. (1) Use short time-step measurements of the exchange of C, water, and energy measured from a flux tower, as well as associated ecological measurements, to document how ecosystem physiology and C flux evolve following forest harvest and how these factors are affected by forest structure and climate for the boreal forest of eastern Canada. Ten years after harvest, our continuous measurements have shown that the ecosystem attained C neutrality for the first time in 2010. We will next test hypotheses about how ecosystem physiology and structure evolve after the point of C neutrality. (2) Integrate data from flux towers and forest inventories with an ecophysiological process model and a model-data fusion framework to evaluate the importance of high-frequency environmental variability on the structure and function of boreal forests in eastern Canada. We will then extend this to larger spatial scales. This work will help establish an analytical framework for incorporating high-frequency environmental variability into future climate assessment reports. (3) Use our airborne lidar and hyperspectral remote sensing package to evaluate the ability of the ICESat GLAS lidar satellite sensor to estimate forest biomass of North America and its sub-regions, particularly the boreal biome. We will determine how tree cover and plant functional type information can be used to determine when the lidar data can be supplemented with other data sources. This work will help provide a statistical and analytical framework for estimating the spatial distribution of regional C stocks.