Date of Award
Master of Forest Resources (MFR)
Bauerle, William L
Wang , Geoff
Toler , Joe
A hybrid model (FVS-BGC) that couples the process-model STAND-BGC to the empirically based forest vegetation simulator (FVS) was parameterized with comprehensive ecophysiological, site, and silvicultural data collected on Acer rubrum L. (A. rubrum), Paulownia elongata (P. elongata), Quercus nuttallii (Q. nuttallii), and Quercus phellos (Q. phellos) in 2006. A series of simulations provided of estimates species-specific carbon gain, growth, and yield under well-watered and water-stressed conditions. Simulations on a species-specific basis allowed assessment of drought effects on stand production and the ability of FVS-BGC to predict on a deciduous species basis. Under well watered conditions, FVS-BGC was able to predict P. elongata, Q. nuttallii and Q. phellos height and caliper. Water deficit conditions were characterized by different maximum volumetric water content parameterization in the model. Under water stress, FVS-BGC accurately predicted height and caliper in Q. nuttallii and Q. phellos. For carbon sequestration, FVS-BGC predictions agreed with measured values on all study species under well watered and water stressed conditions. Thus, this study demonstrates that tree-to-tree variation and different water stress conditions can be characterized in FVS-BGC for accurate predictions of species-specific annual carbon gain, growth, and yield.
Wang, Ying, "Predicting the growth of deciduous tree species in response to water stress: FVS-BGC model parameterization, application and evaluation" (2007). All Theses. 250.