Estimating diameter at breast height and basal diameter of trees from stump measurements in Nepal's lower temperate broad-leaved forests
Multiple linear regression models for predicting diameter at breast height (DBH) and basal diameter (BD) of trees from stump measurements are presented. These models were developed for the lower temperate broad-leaved forests of Nepal's central middle hills. In addition to general prediction mo...
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Published in | Forest ecology and management Vol. 81; no. 1; pp. 75 - 84 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.02.1996
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | Multiple linear regression models for predicting diameter at breast height (DBH) and basal diameter (BD) of trees from stump measurements are presented. These models were developed for the lower temperate broad-leaved forests of Nepal's central middle hills. In addition to general prediction models based on all trees in the sample, specific models for this forest type are presented for small (< 35 cm DBH) and large (⩾ 35 cm DBH) trees, and for two dominant taxa,
Schima wallichii and the genus
Castanopsis. The models were derived from a total of 1304 diameter observations measured on 163 trees in two forests. Diameters were measured on each tree at eight different stem heights (3.0 to 180.0 cm above the ground level), which included BD and DBH (measured at 30.0 and 130.0 cm above the ground level, respectively). In addition, two general simple linear regression models are presented to predict DBH from BD, and vice versa. Cross-validation results indicate good predictive ability, and reliability and validity of the models. Seventeen commonly occurring tree species and ten families were represented in the sample. These models are recommended for general use in the lower temperate broad-leaved forests of the central Himalayas, particularly in those forests dominated by the
Schima-Castanopsis association. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0378-1127 1872-7042 |
DOI: | 10.1016/0378-1127(95)03663-6 |