A multivariate statistical approach to predicting mature tree performance based on seedling characteristics

Abstract

A common objective in commercial reforestation is to plant seedlings that will produce superior adult trees. Long forest management planning horizons and life spans of most forest trees complicate the prediction of growth and performance of adult trees originating from planted seedlings of unknown genetic origin. We used multivariate statistics to identify and rank a set of seedlings characteristics that could predict the performance of mature trees in Pinus ponderosa. Results indicated that metabolic heat rate (q), a measure of total metabolism, of one-year-old foliage during the peak growth in May, was the most important seedling characteristic that predicted mature-tree performance. Increased metabolic heat rate in seedlings corresponded with greater vigor of mature trees. Additionally, seedling basal stem diameter (D), height (H), and needle length (NL), measured in November, were, in order of importance, other variables that defined the vigor class of the mature clones. However, these seedling morphological characteristics correlated negatively with vigor classification of the mature clones, contradicting the notion that greater D and/or H during the seedling stage may indicate a greater vigor at maturity.