Quartered neighbor method: A new distance method for density estimation
Quantitative data are essential to an appropriate characterization of vegetation. In the past few years, considerable attention has been paid to vegetation sampling techniques. A number of methods have been developed for plant density estimations that utilize spacing distances instead of fixed-area...
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Published in | Frontiers of biology in China Vol. 4; no. 4; pp. 574 - 578 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Heidelberg
SP Higher Education Press
01.12.2009
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Subjects | |
Online Access | Get full text |
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Summary: | Quantitative data are essential to an appropriate characterization of vegetation. In the past few years, considerable attention has been paid to vegetation sampling techniques. A number of methods have been developed for plant density estimations that utilize spacing distances instead of fixed-area quadrats. In this paper, we review the main distance methods for estimating density and propose a new distance method denominated the quartered neighbor method. In this method, the sampling point is considered the center, and the area around it is divided into four quadrants. The distance from the closest individual in each quadrant to its closest neighbor in the same quadrant is measured, and the average of them is the distance we need. It is actually an integration of two old distance methods, the nearest neighbor method, and the point-centered quarter method. With our new method and an old distance method (the point-centered quarter method), we calculated the average spacing distances of the
Larix principis-rupprechtii
population in the larch forests of the Donglingshan Mountain. Comparing the two methods with the quadrat method, we found they were almost the same in accuracy, but the precision of the new one was better. Meanwhile, it is adequate in sampling intensity and adaptable for general use in rapid ecological survey work. |
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ISSN: | 1673-3509 1673-3622 |
DOI: | 10.1007/s11515-009-0039-0 |