Effects of climate, forest structure, soil water, & scale on biosphere-atmosphere gas exchange in a Great Lakes mixed-deciduous forest

Our ability to model weather and climate at various spatial and temporal scales is highly dependent on our understanding of the ecosystem parameters that control mass and energy exchange between the biosphere and atmosphere. Over forested canopies, the physical structure of vegetation interacts with the wind by exerting drag on the flow, thus generating turbulent mixing that is necessary for scalar transport. These interactions occur across a variety of spatio-temporal scales (microscopic to global; milliseconds to decades) and their consequences are influential over an equally wide range of spatio-temporal scales. In these studies we used 12 years of flux-tower data and modeling exercises to test the sensitivity of carbon, water, and momentum transfer to climate, canopy structure heterogeneity, soil moisture heterogeneity, time, and scale within a Great Lakes Mixed-Deciduous Forest located at the University of Michigan Biological Station (UMBS).;We first described a data processing, analysis, and gap-filling package for the AmeriFlux-affiliated meteorological stations at UMBS. This data package was then utilized to test the sensitivity of carbon fluxes to climate from 2000-12. We found carbon dynamics to be significantly affected by timescale, dataset length, and within-season and antecedent environmental conditions. We found the use of an artificial neural network (ANN) to model short-term (30-60 min) carbon fluxes was superior to linear-interaction models.;We next used paired (undisturbed and disturbed) forest environments along with a large-eddy simulation (LES), long-term meteorological observations and remote sensing of forest canopy to explore the effects of canopy structure on flux-driving surface roughness parameters, d, z0, and ha. We described long-term observations of ha as a metric for mapping long-term vertical stem growth of the forest. We found observed relationships between roughness parameters and canopy structure to be highly variable. We determined LES to be a suitable method to quantitatively predict the effects of canopy-structure change. We performed a virtual experiment to test the sensitivity of roughness parameters with respect to four axes of variation in canopy structure: (1) leaf area index (LAI), (2) vertical profile of leaf area density (LAD), (3) canopy height, and (4) gap fraction. We found consistent relationships between roughness parameters and LAI and height. The incorporation of canopy-roughness relationships and seasonality to roughness parameter was shown to increase flux model accuracy.;We used RAFLES-ED2, developed and evaluated here, to explore the spatial scaling relationships of evapotranspiration as affected by soil moisture (SM) in heterogeneous environments at the tree-crown scale. We found that RAFLES-ED2 was able to model the sensitivity of biosphere-atmosphere interactions to physiological stress brought on by water-limitations. During non-limiting water conditions, we found cumulative LAI to be the primary driver of crown-scale flux dynamics, while SM began to have a significant influence during water-limiting conditions.