Charles O. Sabatia

Effects of stand density and seedlot on three wood properties of young radiata pine grown at a dry-land site in New Zealand

BackgroundManipulation of stand density and choice of genetic material are two key mechanisms through which forest managers can influence tree growth and wood properties. Past silvicultural practices in New Zealand have been characterised by early thinning to relatively wide spacing, while tree improvement programmes have primarily focussed on growth and form. The aim of this study was to quantify the impacts of stand density and past genetic selections on the wood properties of radiata pine (Pinus radiata D. Don).MethodsStress-wave velocity, wood density, microfibril angle (MFA) and modulus of elasticity (MOE) were measured on trees and wood samples taken from a 15-year-old silvicultural and tree breeds trial located in Canterbury, New Zealand. The focus of this study was comparison of seedlots with genetic ratings of GF6 and GF25. Data from pruned stands with final densities of 100, 200 and 400 stems ha−1 were compared as were data from unpruned stands with stand densities of 200, 400, 600 and 1000 stems ha−1.ResultsStress-wave velocity of trees was affected by final stand density, with the lowest values recorded from trees in the 100 and 200 stems ha−1 treatments. Values for wood MFA and MOE both showed the greatest amount of change when final stand density was less than 400 stems ha−1. Trees from the GF25-rated seedlot had wood density that was approximately 34 kg m−3 lower than trees from the GF6-rated seedlot.ConclusionVery high stand densities are not required in order to influence wood properties, but early thinning to low stand densities should be avoided. Such results are of practical importance to forestry managers.

Calibrated tree counting on remotely sensed images of planted forests

The development of robust and accurate methods for counting trees from remotely sensed data could provide substantial cost savings in forest inventory. A new methodology that provides a framework for calibrating tree detection algorithms to obtain accurate tree counts for even-aged stands is described. The methodology was evaluated using two tree detection algorithms and two operators using airborne laser scanning (ALS) and orthophotograph images for four Pinus radiata D.Don stands ranging in age between 5 and 32 years with stand densities ranging between 204 and 826 stems ha−1. For application of the methodology to ALS images the error of estimate on the total count was 4.7% when calibration counts from actual ground plots were used and 10.5% when calibration counts from virtual plots on the image were used. For orthophotographs, the error of estimate was 6.1% using ground calibration plots and 24.3% using calibration counts from virtual plots. The described methodology was shown to be robust to variations in the process from the two operators and two algorithms evaluated. The measure of accuracy determined using the methodology can be used to provide an objective basis for evaluating a wide range of tree counting and detection processes in future research.