scholarly journals Site-Index Curves and Growth Intercepts for Young White Spruce Plantations in North Central Ontario

2006 ◽  
Vol 23 (4) ◽  
pp. 257-263 ◽  
Author(s):  
Willard H. Carmean ◽  
Gerrit Hazenberg ◽  
James S. Thrower ◽  
Richard R. LaValley
Keyword(s):  
Regression Model ◽  
Nonlinear Regression ◽  
White Spruce ◽  
Analysis Data ◽  
Site Index ◽  
Nonlinear Regression Model ◽  
North Central ◽  
Breast Height ◽  
University Of Wisconsin ◽  
Dominant Height

Abstract Site-index (heightߝgrowth) curves, site-index prediction equations, and growth intercepts were developed from internode measurements and stem-analysis data using dominant trees in 69 plots located in white spruce plantations aged 19 to 32 years total age. Site-index curves were based on breast-height (1.3 m) age because our analyses show that height growth below breast height is slow and erratic and is poorly related to site index (dominant height at 15 years breast-height age). The most precise model for computing heightߝgrowth curves was a Newnham constrained polymorphic expression (Newnham, R.M. 1988. A modification of the Ek-Payandeh nonlinear regression model for site-index curves. Can. J. For. Res. 18:115ߝ120) of the Ek nonlinear regression model (Ek, A.R. 1971. A formula for white spruce site-index curves. University of Wisconsin For. Res. Note 161. 2 p). Comparisons showed that site-index curves in North Central Ontario were comparable to site-index curves for white spruce plantations in southeastern Ontario. The first three to five internodes above 2.0 m gave the most precise estimates of site index based on growth intercepts. North. J. Appl. For. 23(4):257–263.

A modification of the Ek–Payandeh nonlinear regression model for site index curves

1988 ◽  
Vol 18 (1) ◽  
pp. 115-120 ◽  
Author(s):  
R. M. Newnham
Keyword(s):  
Regression Model ◽  
Growth Model ◽  
Nonlinear Regression ◽  
Site Index ◽  
The Other ◽  
Nonlinear Regression Model ◽  
Minimum Loss ◽  
Unconstrained Model ◽  
Pass Through ◽  
Richards Growth Model

A new nonlinear regression model for constructing site index curves is described that, unlike previous models based on the Chapman–Richards growth model, produces sets of curves that are constrained to pass through the appropriate height at the index age as well as through the origin. The model was tested on two sets of height–age data, one from published yield tables and the other from stem analyses, and was found to give a good fit in both cases. There was a minimum loss of accuracy compared with a similar, unconstrained model.

Early Height Growth and Site Index for Planted Red Pine in North Central Ontario

1995 ◽  
Vol 12 (1) ◽  
pp. 23-29
Author(s):  
William H. Carmean ◽  
James S. Thrower
Keyword(s):  
Growth Curves ◽  
Analysis Data ◽  
Site Index ◽  
Height Growth ◽  
Red Pine ◽  
North Central ◽  
Breast Height ◽  
Excellent Growth ◽  
Index Estimation ◽  
Best Estimates

Abstract Height-growth, site-index curves, and growth intercepts were developed from internode and stem-analysis data using dominant trees in 25 plots located in red pine plantations aged 26 to 37 yr. Height-growth curves were based on breast-height age because growth below breast height (1.3 m) was slow and erratic. Growth intercepts using the first three to five internodes above 1.5 m gave the best estimates of site index (dominant height at 20 yr breast-height age)for trees that were between 3 and 5 yr breast-height age; site-index estimation equations gave the best estimates for trees older than 10 yr breast-height age. These computed height-growth curves and growth intercepts and observed site index in north central Ontario were similar to other regions. The excellent growth observed in this study suggests that red pine should be given greater emphasis in future reforestation programs in north central Ontario. North. J. Appl. For. 12(1): 23-29.

Polymorphic height and site index curves for lodgepole pine in Alberta

1989 ◽  
Vol 19 (9) ◽  
pp. 1151-1160 ◽  
Author(s):  
C. J. Cieszewski ◽  
I. E. Bella
Keyword(s):  
Regression Model ◽  
Prior Knowledge ◽  
Nonlinear Regression ◽  
Lodgepole Pine ◽  
Site Index ◽  
The Other ◽  
Nonlinear Regression Model ◽  
Permanent Sample Plots ◽  
Accuracy And Precision ◽  
Pass Through

This new, biologically based, nonlinear regression model produces polymorphic site index and height curves as a function of prediction age and a height at any age. The curves are constrained to pass through the origin and appropriate heights at any index age. The model was parametrized on 970 stem-analyzed trees and tested on tree measurements from 147 permanent sample plots. Compared with other lodgepole pine (Pinuscontorta var. latifolia Engelm.) height models in Alberta, this model had fewer parameters, yet showed better accuracy and precision than the other models. Above all, the new model provides compatible site index and height estimates, and it can predict height without prior knowledge of site index.

Growth intercepts for estimating site quality of young white spruce plantations in north central Ontario

1987 ◽  
Vol 17 (11) ◽  
pp. 1385-1389 ◽  
Author(s):  
James S. Thrower
Keyword(s):  
Average Length ◽  
White Spruce ◽  
Site Index ◽  
Site Quality ◽  
North Central ◽  
Breast Height

Growth intercepts were used to estimate site index (defined as height of the trees 15 years after breast height (1.3 m) was attained) of dominant, planted white spruce (Piceaglauca (Moench) Voss) in north central Ontario. The growth intercepts were computed using four methods to select internode lengths from series of one through seven internodes, starting at each of eight heights from 0 to 3.0 m. Precision increased rapidly with more internodes and higher starting heights but quickly slowed to only marginal increases. Removing the smallest internode increased precision when growth intercepts started below 1.3 m. Removing the largest and both the smallest and largest internodes reduced precision from all starting heights. The most precise and practical growth intercepts used the average length of the first three, four, and five internodes above 2.0 m, explaining 83, 85, and 89% of the variation in site index, respectively.

Linking juvenile growth of white spruce with site index

2006 ◽  
Vol 82 (6) ◽  
pp. 819-824 ◽  
Author(s):  
Zhili Feng ◽  
Kenneth J Stadt ◽  
Victor J Lieffers ◽  
Shongming Huang
Keyword(s):  
White Spruce ◽  
Analysis Data ◽  
Site Index ◽  
Growth Increment ◽  
Breast Height ◽  
Spruce Stands ◽  
Stand Height ◽  
Using Data ◽  
New Equation ◽  
Mixedwood Stands

The goal of this study was to link the growth of juvenile white spruce stands with an estimate of their site index. We applied a previously developed technique for correcting the height bias created by dominance switching among juvenile trees before trees reached the site index base age (50 years at breast height), using stem analysis data of white spruce from five mixedwood stands in central Alberta. For white spruce of approximately 15 years total age, we found the height of the current top height trees was approximately 14% greater than the height of the top height trees that would be selected close to breast height age 50. This height correction is essential to avoid an overestimate of site index. Secondly, to avoid the difficulties of determining breast height age or growth increment required for juvenile site index determination, we developed a linkage to site index using data from 168 white spruce trees that were longitudinally sectioned along the pith, selected from juvenile (age 6–15) spruce stands. Using this new equation, coupled with the correction for bias, we found that site index for white spruce from 49 test stands in Alberta, ranged from 9.0 to 31.8 m at base age 50, with a mean of 17.8 m; these values are in the range for spruce in mixedwood stands in Alberta. Key words: juvenile stand, height age curve, height bias adjustment, site index

scholarly journals Dimension Analysis-Based Model for Prediction of Shale Compressive Strength

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xiangyu Fan ◽  
Fenglin Xu ◽  
Lin Chen ◽  
Qiao Chen ◽  
Zhiwei Liu ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Regression Model ◽  
Nonlinear Regression ◽  
Prediction Error ◽  
Diameter Ratio ◽  
Nonlinear Regression Model ◽  
Average Prediction Error ◽  
Model Average ◽  
Dimension Analysis ◽  
Longmaxi Shale

The compressive strength of shale is a comprehensive index for evaluating the shale strength, which is linked to shale well borehole stability. Based on correlation analysis between factors (confining stress, height/diameter ratio, bedding angle, and porosity) and shale compressive strength (Longmaxi Shale in Sichuan Basin, China), we develop a dimension analysis-based model for prediction of shale compressive strength. A nonlinear-regression model is used for comparison. A multitraining method is used to achieve reliability of model prediction. The results show that, compared to a multi-nonlinear-regression model (average prediction error = 19.5%), the average prediction error of the dimension analysis-based model is 19.2%. More importantly, our dimension analysis-based model needs to determine only one parameter, whereas the multi-nonlinear-regression model needs to determine five. In addition, sensitivity analysis shows that height/diameter ratio has greater sensitivity to compressive strength than other factors.

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