Weighted linear regression using D2H and D2 as the independent variables

Schreuder, Hans T.; Williams, Michael S.

doi:10.2737/rmrs-rp-6

Cited by 4 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Assumptions of heteroscedasticity were also evaluated through residual plots and Furnival's Index of Fit, and for biomass and volume prediction models heteroscedasticity was corrected using the combined variable D 2 H (where D is diameter at breast height and H is total tree height) [51] as a weight. Use of D 2 H as a regression or weight variable in forestry has been summarized by Schreuder, et al [52] who concluded that more complex variable forms provided no advantage over the simple combined variable. Linear, exponential, and power function model forms were compared using Furnival's Index of Fit to determine best weighted models.…”

Section: Statistical Analysesmentioning

confidence: 99%

Loblolly Pine Growth Patterns on Reclaimed Mineland: Allometry, Biomass, and Volume

Priest

Stovall

Coble

et al. 2015

Forests

View full text Add to dashboard Cite

Surface lignite coal mines in east Texas are commonly reforested using loblolly pine (Pinus taeda L.) following mining and reclamation activities. Due to the nature of such an extreme disturbance, altered growth patterns, growth rates, and productivity could be expected. We destructively sampled above-and belowground tissue to develop prediction equations specific to these sites. These prediction equations differed statistically from those found in the literature regarding unmined land. At the stand level, biomass and volume productivity appeared similar with young stands on reclaimed mineland performing slightly poorer than similarly managed unmined sites. Allometric partitioning of above-and belowground biomass differed statistically from the unmined allometric model previously studied. The allometric pattern on reclaimed mineland indicated greater partitioning of biomass belowground for young stands of low quadratic mean diameter relative to unmined stands. Older stands on reclaimed mineland exhibited no allometric partitioning differences from unmined stands, indicating the normal allometric pattern is resumed for stands greater than 10 years of age.

show abstract

Section: Statistical Analysesmentioning

confidence: 99%

Loblolly Pine Growth Patterns on Reclaimed Mineland: Allometry, Biomass, and Volume

Priest

Stovall

Coble

et al. 2015

Forests

View full text Add to dashboard Cite

show abstract

Estimating carbon storage in windbreak trees on U.S. agricultural lands

et al. 2016

View full text Add to dashboard Cite

Assessing carbon (C) capture and storage potential by the agroforestry practice of windbreaks has been limited. This is due, in part, to a lack of suitable data and associated models for estimating tree biomass and C for species growing under more opengrown conditions such as windbreaks in the Central Plains region of the United States (U.S.). We evaluated 15 allometric models using destructively sampled Pinus ponderosa (Lawson & C. Lawson) data from field windbreaks in Nebraska and Montana. Several goodness-of-fit metrics were used to select the optimal model. The Jenkins' et al. model was then used to estimate biomass for 16 tree species in windbreaks projected over a 50 year time horizon in nine continental U.S. regions. Carbon storage potential in the windbreak scenarios ranged from 1.07 ± 0.21 to 3.84 ± 0.04 Mg C ha -1 year -1 for conifer species and from 0.99 ± 0.16 to 13.6 ± 7.72 Mg C ha -1 year -1 for broadleaved deciduous species during the 50 year period. Estimated mean C storage potentials across species and regions were 2.45 ± 0.42 and 4.39 ± 1.74 Mg C ha -1 year -1 for conifer and broadleaved deciduous species, respectively. Such information enhances our capacity to better predict the C sequestration potential of windbreaks associated with whole farm/ranch operations in the U.S.

show abstract

Comprehensive Regional Resource Assessments and Multipurpose Uses of Forest Inventory and Analysis Data, 1976 to 2001: A Review

Rudis¹

2003

View full text Add to dashboard Cite

Weighted linear regression using D2H and D2 as the independent variables

Abstract: This file was created by scanning the printed publication.Errors identified by the software have been corrected; however, some errors may remain.

Cited by 4 publications

References 5 publications

Loblolly Pine Growth Patterns on Reclaimed Mineland: Allometry, Biomass, and Volume

Loblolly Pine Growth Patterns on Reclaimed Mineland: Allometry, Biomass, and Volume

Estimating carbon storage in windbreak trees on U.S. agricultural lands

Comprehensive Regional Resource Assessments and Multipurpose Uses of Forest Inventory and Analysis Data, 1976 to 2001: A Review

Contact Info

Product

Resources

About