The Allometry of Coarse Root Biomass: Log-Transformed Linear Regression or Nonlinear Regression?
Published 2013 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
The Allometry of Coarse Root Biomass: Log-Transformed Linear Regression or Nonlinear Regression?
Authors
Keywords
Trees, Forests, Biomass (ecology), Forest ecology, Arithmetic, Pines, Linear regression analysis, Statistical distributions
Journal
PLoS One
Volume 8, Issue 10, Pages e77007
Publisher
Public Library of Science (PLoS)
Online
2013-10-09
DOI
10.1371/journal.pone.0077007
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A general combined model to describe tree-diameter distributions within subtropical and temperate forest communities
- (2013) Jiangshan Lai et al. OIKOS
- Allometric models for estimating above- and below-ground biomass in Amazonian forests at São Gabriel da Cachoeira in the upper Rio Negro, Brazil
- (2012) Adriano José Nogueira Lima et al. FOREST ECOLOGY AND MANAGEMENT
- Evaluating model fit to determine if logarithmic transformations are necessary in allometry: A comment on the exchange between Packard (2009) and Kerkhoff and Enquist (2009)
- (2012) Ford Ballantyne JOURNAL OF THEORETICAL BIOLOGY
- Topographic Variation in Aboveground Biomass in a Subtropical Evergreen Broad-Leaved Forest in China
- (2012) Dunmei Lin et al. PLoS One
- Coarse root biomass allometric equations for Abies balsamea, Picea mariana, Pinus banksiana, and Populus tremuloides in the boreal forest of Ontario, Canada
- (2011) Brian W. Brassard et al. BIOMASS & BIOENERGY
- Minimizing Bias in Biomass Allometry: Model Selection and Log-Transformation of Data
- (2011) Joseph Mascaro et al. BIOTROPICA
- Rotational distortion in conventional allometric analyses
- (2011) Gary C. Packard COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY A-MOLECULAR & INTEGRATIVE PHYSIOLOGY
- On the use of log-transformation vs. nonlinear regression for analyzing biological power laws
- (2011) Xiao Xiao et al. ECOLOGY
- Fitting statistical models in bivariate allometry
- (2010) Gary C. Packard et al. BIOLOGICAL REVIEWS
- Estimation of root biomass based on excavation of individual root systems in a primary dipterocarp forest in Pasoh Forest Reserve, Peninsular Malaysia
- (2010) Kaoru Niiyama et al. JOURNAL OF TROPICAL ECOLOGY
- Allometric equations for predicting body mass of dinosaurs: a comment on Cawley & Janacek (2010)
- (2010) G. C. Packard et al. JOURNAL OF ZOOLOGY
- Influence of Environmental Variability on Root Dynamics in Northern Forests
- (2009) Brian W. Brassard et al. CRITICAL REVIEWS IN PLANT SCIENCES
- Species-habitat associations change in a subtropical forest of China
- (2009) Jiangshan Lai et al. JOURNAL OF VEGETATION SCIENCE
- On allometric equations for predicting body mass of dinosaurs
- (2009) G. C. Cawley et al. JOURNAL OF ZOOLOGY
- Allometric Models for Predicting Aboveground Biomass in Two Widespread Woody Plants in Hawaii
- (2008) Creighton M. Litton et al. BIOTROPICA
- Allometric equations for tree species and carbon stocks for forests of northwestern Mexico
- (2008) José Návar FOREST ECOLOGY AND MANAGEMENT
- A comparison of methods for fitting allometric equations to field metabolic rates of animals
- (2008) Gary C. Packard et al. JOURNAL OF COMPARATIVE PHYSIOLOGY B-BIOCHEMICAL SYSTEMIC AND ENVIRONMENTAL PHYSIOLOGY
- Traditional allometric analysis fails to provide a valid predictive model for mammalian metabolic rates
- (2008) G. C. Packard et al. JOURNAL OF EXPERIMENTAL BIOLOGY
- On the use of logarithmic transformations in allometric analyses
- (2008) Gary C. Packard JOURNAL OF THEORETICAL BIOLOGY
- Multiplicative by nature: Why logarithmic transformation is necessary in allometry
- (2008) Andrew J. Kerkhoff et al. JOURNAL OF THEORETICAL BIOLOGY
- Global cost estimates of reducing carbon emissions through avoided deforestation
- (2008) G. Kindermann et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started