Growth and survival as a function of neighborhood density and dbh
A linear, multiple regression was used to relate growth to six variables: four measures of local neighborhood density, and elevation. Trees were divided into four size categories, 2-5, 5-10, 10-20, and 20+ cm dbh (each category open on the right, so ≥ 5 and < 10, etc.). This allowed each size category to have different responses. Stem diameter was included as a predictor within each category because growth changes considerably with size, especially in small trees. Growth was calculated in five census intervals, each lasting five years, and the census was included in the model as a random effect, accounting for the repeated growth measurements of the same individual trees. The models were run separately in the two species, Q. macrocarpa andQ. ellipsoidalis , meaning there were eight models all told, four dbh categories in two species. The survival model was parallel in all aspects, but with logistic regression replacing linear regression.