Forest ecosystems world-over are going through rapid structural changes. These crown-scale changes may extend over large spatial domains. However, the consequences of changes to small-scale canopy structure are not currently incorporated in simulations. The goal of this work is to advance the modeling of transpiration and carbon assimilation in forest environments by incorporating a process-based parameterization of the individual-plant-level hydrodynamics for regional-scale modeling of transpiration, and CO2.
The hydraulic architecture of trees determines the movement of water through forest ecosystems into the atmosphere. Though hydraulic limitations to stomatal conductance and gas exchange in forest ecosystems are common, current models for transpiration do not dynamically resolve tree-scale hydraulics of trees and cannot take advantage of recent remote-sensing driven advances that measure tree-crown characteristics. The Finite-Elements Tree-Crown Hydrodynamics (FETCH) model provides a dynamic representation of tree hydraulics. This work will further develop FETCH, which can resolve midday stomatal closure, and other hydraulic-stress related phenomena. FETCH will be dynamically coupled with the Ecosystem Demography model (ED2) which resolves momentum, heat and gas exchange, and ecosystem dynamics in age-size structured statistically representative tree cohorts. Current methods for image analysis allow tree-crown detection and characterization from high resolution remote sensing images. Allometric relationships will be used to scale these into individual 3-D representations of the hydraulic systems of representative size cohorts. We propose to use this method to derive the effective tree-scale structures from IKONOS images, verified against explicit meter-scale lidar measurements. Extensive long-term data from the Duke Forest, Harvard Forest and UMBS will be used for parameterization of the system. Regional atmospheric simulations, driving the coupled ED-FETCH system will be used to estimate the impacts of satellite detected canopy-structure on hydrodynamic limitations to transpiration, and will provide a tool for simulations of canopy structure and forest management on carbon exchange at the ecosystem scale.
Study Site Overview
The UMBS Forest Ecosystem STudy (UMBS-FEST) occupies >200 ha of mostly forested landscape along the south shore of Douglas Lake, Michigan (Cheboygan County). Within this landscape, ~35 ha of forest has been experimentally manipulated to accelerate a successional change already occurring on the landscape: the senescence of early-successional aspen and birch trees, and their replacement by longer-lived oak, maple, and pine. Aspen and birch were the principal colonizers of extensive cutover and burned lands throughout the upper Great Lakes region about a century ago, and today forests dominated by these species cover >100,000 km2 in the region.
Most of our data collection occurs in permanent plots distributed among reference (unmanipulated) and treatment (accelerated succession) areas of the landscape. Plots in the treatment area are quantitatively paired with reference plots of similar tree species composition, based on a principal components analysis of leaf litterfall. See the map below, which identifies these plot pairs with common symbols.
The central, 1.1 ha plots surrounding the two eddy flux towers accommodate our most intensive measurements. Line power supports an array of electronic equipment continuously measuring air and soil climatic parameters, incoming radiation and other components of the energy budget, and water vapor and CO2 gradients extending from the forest floor up through the forest canopy. The 1.1 ha plots are also home to the most intensive biometric measurements in our studies. Within these two plots, we make measurements of tree biomass production, chemistry, and belowground processes on and adjacent to individual trees, in order to understand fine-scale spatial variation in the processes that scale up to drive stand- and landscape-level ecosystem functions like water use, C storage, and N retention. We replicate many process measurements within and between the spatially extensive 0.08 ha plots to quantify stand-level variation in biogeochemical cycling, and to understand the aggregated effects of forest succession on biogeochemistry across multiple stand types.