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Use of Logarithmic Regression in the Estimation of Plant Biomass
Abstract
The basic assumptions of regression analysis are recalled with special reference to the use of a logarithmic transformation. The limitations imposed on inference-making by failure to comply with these assumptions are discussed and ways to avoid the limitations indicated. A systematic bias of the order of 10 to 20% which is inherent in most, if not all, prior uses of the logarithmic equation to estimate plant biomass is noted as is the correction for the bias.
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Cited by
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Rate of tree carbon accumulation increases continuously with tree size
Stephenson, N. L., Das, A. J., Condit, R., Russo, S. E., Baker, P. J., Beckman, N. G., Coomes, D. A., Lines, E. R., Morris, W. K., Rüger, N., et al. (2014) · Nature · doi:10.1038/nature12914 · Cited by 897
Allometric equations for integrating remote sensing imagery into forest monitoring programmes
Jucker, T., Caspersen, J., Chave, J., Antin, C., Barbier, N., Bongers, F., Dalponte, M., van Ewijk, K. Y., Forrester, D. I., Haeni, M., et al. (2017) · Global Change Biology · doi:10.1111/gcb.13388 · Cited by 405
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Metadata
- Authors
- Baskerville, G. L.
- Venue
- Canadian Journal of Forest Research
- Publisher
- Canadian Science Publishing
- Published
- 1972-03-01
- Volume
- 2
- Issue
- 1
- Pages
- 49-53
- ISSN
- 0045-5067 (ISSN-L)
- 1208-6037
- OpenAlex
- W2098935748
- Cited by
- 1,158
- References
- 0
- FWCI
- 6.33
- Type
- journal article
- Language
- en
- Open access
- closed
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- Baskerville, G. L. (1972). Use of Logarithmic Regression in the Estimation of Plant Biomass. Canadian Journal of Forest Research. https://doi.org/10.1139/x72-009
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
