The goal of this phase of the Forest Ecosystem Dynamics (FED) project is to use forest succession models, soil process models, and radiation scattering models, combined with ground-based and remotely sensed observations, to improve understanding of the dynamics of northern/boreal forest ecosystems over a range of spatial and temporal scales. The repetitive, multi-scale, and multi-spectral observation capabilities afforded by remote sensing platforms make this type of data one of the premier tools for the assessment of global change. The changes to be detected are ecosystem dynamics expressed as scale dependent patterns. To make inferences about changes in underlying ecological processes, detectable features and patterns must be linked to explanations involving well-understood pattern generating mechanisms. The FED project emphasizes detection of features and pattern at local to regional spatial scales (10 to 10,000 meters) and exploration of mechanisms involving temporal scales ranging from those of physiological processes to long term ecological processes (10^-4 to 10^3 years). The underlying thesis of the FED project is that through careful observation, experimentation, and modeling, the interactions of the vegetation, soil, and energy components of the forest ecosystem can be understood and potentially detectable responses to climate change or other disturbances predicted.
Our approach in Phase II of the FED Project is to develop a modeling workbench that can link individual submodels of forest physiology, growth and succession, soil processes, and the radiation regime within and external to the forest/soil complex. These linked models are to be used in combination with ground-based, airborne and satellite observations, to better understand the dynamics of forest ecosystem evolution. By the end of Phase II, we will be able to predict multi-spectral response (optical and microwave) from simulated forest ecosystems for a variety of conditions, and as such, have a sensitive indicator of both direction and magnitude of ecosystem change.
Emphasis will be placed on using this integrated approach to test hypotheses about process interactions, and spatial and temporal scaling related to global change. This hypothesis testing will occur as we: (a) complete the logical and functional integration of the various process sub-models using an "object-oriented" approach; (b) analyze the extensive ground-based, airborne, and satellite data sets which have been acquired in order to derive the products which are needed as inputs to the models and are useful in improving our understanding of ecosystem processes; and (c) rigorously validate both the sub-models and integrated models by comparing model-derived results with ground-based and remote observations.