Minna Pulkkinen. (2012). On non-circularity of tree stem cross-sections: effect of diameter selection on cross-section area estimation, Bitterlich sampling and stem volume estimation in Scots pine. Silva Fennica vol. 46 no. 5B article id 924. https://doi.org/10.14214/sf.924

Keywords: basal area; Scots pine; stem volume; forest mensuration; cross-section; non-circularity; Bitterlich sampling

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In the common methods of forest mensuration, including stem volume models and Bitterlich sampling, stem cross-sections are assumed to be circular. In nature this assumption is never exactly fulfilled. Errors due to non-circularity have been presumed to be small and unimportant but studied little: theoretical and empirical studies exist on cross-section area estimation, but errors in stem volume estimation have not been investigated at all, and errors in Bitterlich sampling are theoretically known only for stand basal area estimation. In the theoretical part of this study, we developed methods for quantifying the systematic and sampling errors that 22 common ways of selecting diameter within non-circular cross-sections induce (i) in area estimates by the circle area formula, (ii) in stand total estimates by Bitterlich sampling, and (iii) in stem volume estimates by a volume equation, by a cubic-spline-interpolated stem curve, and by a generalised volume estimator. In the empirical part, based on the digital images of 709 discs taken at 6–10 heights in 81 Scots pine stems from different parts of Finland, we investigated the variation in cross-section shape, and demonstrated the magnitude of the errors presented in the theoretical part. We found that non-circularity causes systematic overestimation of area and volume, and inflicts potentially systematic error on stand total estimates by Bitterlich sampling. In our data these effects were small, but the finding is not generalisable due the skewed size distribution and poor geographical representativeness of the data. We recommend using diameter derived from girth for both tree and stand level estimation, as it involves no sampling error and produces clearly the most stable systematic errors.

Pulkkinen, E-mail: minna.pulkkinen@iki.fi

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