Use of a land classification system in growth and yield prediction on the Cumberland Plateau of Tennessee

Growth and yield predictors are a significant aid to foresters developing management plans. Stand level yield modeling has been well developed for even-aged stands of a single species. However, much planning for forest management is concerned with mixed species stands which may be even-aged or uneven-aged. Much of the Cumberland Plateau of Tennessee is in mixed hardwoods for which there are no applicable growth and yield predictors. Use of site index as a variable in growth and yield prediction models is limited in most stands because their history is not known and many may not be evenaged. Landtypes may offer an alternative to site index for these mixed stands because they were designed to include land of about equal productivity.

Data from 399 Forest Inventory and Analysis plots, collected by Southern Forest Experiment Station (SFES), Forest Service, USDA, were utilized in this study. To determine vegetation by landtype, dependency between landtype and detailed forest type was tested with Chi-square. Differences in productivity among landtypes was tested by employing regression analyses and analysis of variance (ANOVA). Basal area growth was fitted to the nonlinear models developed by Moser and Hall (1969). Basal area growth and volume growth were also predicted as a function of initial total basal area and initial volume with linear regression by landtype and by landtype class. Differences in basal area growth and volume growth by landtype were tested with ANOVA. Dependency between site class and landtype was tested with Chi-square.

Vegetation types seem to be related to landtypes in the study area although the validity of the test is questionable because of a high proportion of sparsely occupied cells. No statistically significant differences in productivity among landtypes were found in this study. This may be because the data were from plots installed and maintained to monitor regional forest growth, or due to the absence of real differences. A study installed specifically to test for differences in productivity by landtype is recommended.