| dc.creator | Ritchie, Martin W. | |
| dc.creator | Hann, David W. | |
| dc.creator | Oregon State University. Forest Research Laboratory | |
| dc.date.accessioned | 2008-03-31T22:44:26Z | |
| dc.date.available | 2008-03-31T22:44:26Z | |
| dc.date.issued | 1987-03 | |
| dc.identifier.uri | http://hdl.handle.net/1957/8246 | |
| dc.description | Equations are presented for predicting height to crown base (or bole ratio) for fourteen species of trees common to the mixed-conifer zone of southwest Oregon. Nonlinear regression was used to fit a weighted logistic function for each species. The independent variables include height, crown competition factor in larger trees, stand basal area, site index, and diameter divided by height. Although a number of alternative model forms were considered, the logistic function was found to fit the data best. Validation of the model indicated possible difficulties with ponderosa pine and golden chinkapin, but these problems are probably due to inconsistencies in the validation data rather than shortcomings in the individual models. | en |
| dc.format.extent | 2705480 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | en |
| dc.publisher | Corvallis, OR : Forest Research Laboratory, College of Forestry, Oregon State University | en |
| dc.relation.ispartofseries | Research paper (Oregon State University. Forest Research Laboratory) | en |
| dc.relation.ispartofseries | 50 | en |
| dc.subject.lcsh | Forests and forestry -- Oregon, Southwest -- Measurement | en |
| dc.subject.lcsh | Trees -- Oregon, Southwest -- Growth | en |
| dc.title | Equations for predicting height to crown base for fourteen tree species in southwest Oregon | en |
| dc.type | Technical Report | en |
| dc.description.digitization | Master files scanned at 600 ppi (256 Grayscale) using Capture Perfect 3.0 on a Canon DR-9080C in TIF format. PDF derivative scanned at 300 ppi (256 Grayscale), using Capture Perfect 3.0, on a Canon DR-9080C. CVista PdfCompressor 3.1 was used for pdf compression and textual OCR. | en |