Bronson P. Bullock

Juvenile diameter distributions of loblolly pine characterized by the two-parameter Weibull function

Diameter distributions of juvenile loblolly pine (Pinus taeda L.) were characterized utilizing a two-parameter Weibull distribution to aid in forecasting and simulation of young stands. Juvenile diameter distributions were studied to gain insight into the effects of various stand-level factors. Results show that diameter distributions in juvenile loblolly pine stands can be successfully characterized with the two-parameter Weibull function. Repeated measures analysis detected significant planting density, age, and age by planting density interaction effects for the scale and shape parameter estimates from the two-parameter Weibull distribution. Using parameter recovery techniques, estimated diameter distributions were derived from easily attainable stand-level characteristics (i.e. basal area per hectare, planting density, age, and quadratic mean diameter). A thorough understanding of juvenile diameter distributions should prove especially useful for operational planning of stands on short rotations that require estimates of productivity at early ages.

An Evaluation of Selection for Volume Growth in Loblolly Pine

Abstract Total inside-bark volume is the most important selection criterion for productivity in tree breeding programs in the Southeastern U.S. Tree breeders typically estimate total inside-bark volume based on outside-bark diameter at breast height and total height without accounting for stem taper or bark thickness. To make a direct determination of total inside- and outside-bark volume, a loblolly pine (Pinus taeda L.) open-pollinated family trial replicated with cultural treatments of weed control and fertilization was measured. This direct measurement was compared to typical volume estimates. In this trial, approximately 40 individuals from each of 25 open-pollinated first- and second-generation families were destructively sampled in the 13th growing season. Selection for volume using a combined-variable (diameter2 * height) equation was found to be highly effective for making volume gain. There was a high correlation between estimated and directly-measured total inside-bark volumes (0.99). Bark thickness and stem taper had low importance for stem volume selection. There was a positive genetic correlation between bark thickness and diameter at breast height (0.66). This indicates that selection for larger diameters may produce individuals with thicker bark, which may eventually affect total inside-bark volume estimates.

Spatial correlation matrix selection using Bayesian model averaging to characterize inter-tree competition in loblolly pine trees

Many applications of statistical methods for data that are spatially correlated require the researcher to specify the correlation structure of the data. This can be a difficult task as there are many candidate structures. Some spatial correlation structures depend on the distance between the observed data points while others rely on neighborhood structures. In this paper, Bayesian methods that systematically determine the ‘best’ correlation structure from a predefined class of structures are proposed. Bayes factors, Highest Probability Models, and Bayesian Model Averaging are employed to determine the ‘best’ correlation structure and to average across these structures to create a non-parametric alternative structure for a loblolly pine data-set with known tree coordinates. Tree diameters and heights were measured and an investigation into the spatial dependence between the trees was conducted. Results showed that the most probable model for the spatial correlation structure agreed with allometric trends for loblolly pine. A combined Matern, simultaneous autoregressive model and conditional autoregressive model best described the inter-tree competition among the loblolly pine tree data considered in this research.