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Title: Perpendicular distance sampling: an alternative method for sampling downed coarse woody debris
Author: Williams, Michael S.; Gove, Jeffrey H.;
Source: Canadian Journal of Forest Research. 33: 1564-1579
Publication Series: Miscellaneous Publication
Description: Coarse woody debris (CWD) plays an important role in many forest ecosystem processes. In recent years, a number of new methods have been proposed to sample CWD. These methods select individual logs into the sample using some form of unequal probability sampling. One concern with most of these methods is the difficulty in estimating the volume of each log. A new method of sampling CWD that addresses this issue is proposed. This method samples each log with probability proportional to the volume of each piece of CWD. While this method generally has a smaller variance than the existing methods, the primary advantage is that a design-unbiased estimator of CWD volume is achieved without ever actually measuring the volume of any logs. This method, referred to as perpendicular distance sampling (PDS), is compared with three existing sampling techniques for CWD using a simulation study on a series of artificial populations. In every case, the variance of the PDS estimator of CWD volume was smaller than the variance of the competing methods, but the difference in the variance was not large between PDS and two of the competing methods. When estimating the number of pieces of CWD, the variance of the PDS estimator was one of the largest amongst the tested methods. An equally important result is that the variant of line intersect sampling used in this study, where the orientation of the line is the same at all sample points, performed poorly in every situation. This and other problems suggest that the suitability of this sampling technique for estimating CWD is questionable.
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Williams Michael S.; Gove, Jeffrey H. 2003. Perpendicular distance sampling: an alternative method for sampling downed coarse woody debris. Canadian Journal of Forest Research. 33: 1564-1579
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