Inventory estimates of stem volume using nine sampling methods in thinned Pinus radiata stands, New Zealand

Abstract

Simulation is an established tool for examining the efficacy of forestry sampling designs yet there is little empirical information on the effect that spatial layout of a sample has on stand-level inventory of managed, even-aged stands. This simulation study examines the performance of nine different sampling methods in terms of bias and reliability. Data sets, derived from five stands of radiata pine, consisted of census lists of every stem, including the location of each stem, breast-height diameter over-bark (DBH), height and derived volume. In four small stands, stems had been geo-located using ground-based methods, whereas the data for a larger stand were derived from an Airborne Laser Scanning data set. Nine sampling methods (random, stand-boundary, quasi-random, Zigzag transects, grid-based plots of four sizes and single-point) were simulated and applied repeatedly to each stand, and the bias and reliability of the estimate of mean stem volume calculated. Sampling the stand boundary produced a biased estimate, averaging a 12% over-estimate for the four stands aged 22 years or more. The other sampling methods generally showed little bias with most estimates within ±0.5% of the population mean, although the Single-point method was considerably less accurate. The Stand-boundary, Grid-plot (>0.02 ha), and Single-point methods produced unreliable confidence intervals. Most sampling methods showed little bias and good reliability when analysed as simple random samples. Sampling plots in the range of 0.02 to 0.04 ha, located systematically on a grid with random orientation and origin, produced some of the most unbiased and reliable estimates. However, the Zigzag method may be appropriate in small stands as it produces little bias, good reliability and is likely to be operationally efficient.