Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands

Tarquinio Mateus Magalhães; Thomas Seifert

doi:doi:10.11648/j.ajaf.20150305.11

| Peer-Reviewed

Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands

Tarquinio Mateus Magalhães, Thomas Seifert

Published in American Journal of Agriculture and Forestry (Volume 3, Issue 5)

Received: 11 July 2015 Accepted: 18 July 2015 Published: 29 July 2015

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Frequently, biomass expansion factors (BEFs), the respective biomass densities, and their uncertainties are computed without taking into account the appropriate estimators. The objective of this study was to compare the estimates of BEF, BEF-based biomass densities, and their uncertainties using different estimators (mean-of-ratios, ratio-of-means, and regression estimators) in double sampling. Our results demonstrated that increased uncertainty is associated with regression-based biomass densities, and that the computation of BEF using merchantable timber volume should utilize regression estimators, not the usual ratio estimators, which preferably, should be avoided altogether, as they are found to be subjective and more susceptible to errors and personal judgment.

Published in	American Journal of Agriculture and Forestry (Volume 3, Issue 5)
DOI	10.11648/j.ajaf.20150305.11
Page(s)	161-170
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Tree Component, Additivity, Belowground Biomass, Aboveground Biomass, Biomass Expansion Factor (BEF), Androstachys Johnsonii Prain

References

[1]	F. Freese, Elementary Forest Sampling, United States Department of Agriculture, Washington DC; 1962.
[2]	W. G. Cochran, Sampling Techniques, John Wiley & Sons, New York, 3rd edition, 1977.
[3]	F. Freese, Statistics for Land Managers, Paeony Press, Edinburgh, 1984.
[4]	P. G. de Vries, Sampling Theory for Forest Inventory, Springer-Verlag, New York, 1986.
[5]	K. Jayaraman, A Statistical Manual for Forestry Research, FORSPA-FAO, Bangkok, 2000.
[6]	B. Husch, T. W. Beers, and J. A. Kershaw Jr., Forest Mensuration, John Wiley & Sons, New York, USA, 4th edition, 2003.
[7]	A. Jalkanen, R. Mäkipää, G. Stahl, A. Lehtonen, and H. Petersson, “Estimation of the biomass stock of trees in Sweden: comparison of biomass equations and age-dependent biomass expansion factors”, Ann. For. Sci., vol. 62, pp. 845–851, 2005.
[8]	I. Dutca, I. V. Abrudan, P. T. Stancioiu, V. Blujdea, “Biomass conversion and expansion factors for young Norway spruce (Picea abies (L.) Karst.) trees planted on non-forest lands in Eastern Carpathians”, Not Bot Hort Agrobot Cluj, vol. 38, no. 3, pp. 286–292, 2010.
[9]	I. Marková, and R. Pokorný, “Allometric relationships for the estimation of dry mass of aboveground organs in young highland Norway spruce stand”, Acta Univ Agric Silvic Mendel Brun, vol. 59, no. 6, pp. 217–224, 2011.
[10]	E. M. Nogueira, P. M. Fearnside, B. W. Nelson, R. I. Barbosa, and E. W. H. Keizer, “Estimates of forest biomass in the Brazilian Amazon: New allometric equations and adjustments to biomass from wood-volume inventories”, Forest Ecology and Management, vol. 256, pp. 1853–1867, 2008.
[11]	A. Lehtonen, R. Mäkipää, J. Heikkinen, R. Sievänen, and J. Lisk, “Biomass expansion factors (BEFs) for Scots pine, Norway spruce and birch according to stand age for boreal forests”, . Forest Ecology and Management, vol. 188, pp. 211–224, 2004.
[12]	P. Soares, and M. Tome, “Biomass expansion factores for Eucalyptus globulus stands in Portugal”, Forest Systems, vol. 21, no. 1, pp. 141-152, 2012.
[13]	J. J. N. Cháidez, “Allometric equations and expansion factors for tropical dry forest trees of Eastern Sinaloa, Mexico”, Trop Subtrop Agroecosys, vol. 10, pp. 45–52, 2009.
[14]	F. M. Silva-Arredondo, and J. J. N. Návar-Cháidez, “Factores de expansión de biomasa en comunidades florestales templadas del Norte de Durango, México”, Rev Mex Cien For, vol. 1, no. 1, pp. 55–62, 2010.
[15]	S. Brown, “Measuring carbon in forests: current and future challenges”, Environ Pollut, vol. 116, pp. 363–372, 2002.
[16]	P. E. Levy, S.E. Hale, and B. C. Nicoll, “Biomass expansion factors and root: shoot ratios for coniferous tree species in Great Britain”, Forestry, vol. 77, no. 5, pp. 421–430, 2004.
[17]	Z. Somogyi, E. Cienciala, R. Mäkipää, P. Muukkonen, A. Lehtonen, and P. Weiss, “Indirect methods of large-scale forest biomass estimation”, Eur J Forest Res, vol. 126, pp. 197–207, 2007.
[18]	P. N. Edwards, and J. M. Christie, Yield models for forest management, HMSO, London, 1981.
[19]	A. Lehtonen, E. Cienciala, F. Tatarinov, R. Mäkipää, “Uncertainty estimation of biomass expansion factors for Norway spruce in the Czech Republic”, Ann For Sci, vol. 64, pp. 133–140, 2007.
[20]	K. Black, B. Tobin, G. Siaz, K. A. Byrne, and B. Osborne, “Improved estimates of biomass expansion factors for Sitka spruce”, Irish Forestry, pp. 50–65, n.d.
[21]	J. Mantilla, and R. Timane, Orientação para maneio de mecrusse, SymfoDesign Lda, Maputo, Mozambique, p. 1, 2005.
[22]	Dinageca, Mapa Digital de Uso e Cobertura de Terra, Cenacarta, Maputo, Moçambique, 1990.
[23]	Mae, Perfil do Distrito de Chibuto, Província de Gaza, Mae, Maputo, Moçambique, 2005.
[24]	Mae, Perfil do Distrito de Mandhlakaze, Província de Gaza, Mae, Maputo, Moçambique, 2005.
[25]	Mae, Perfil do Distrito de Panda, Província de Inhambane, Mae, Maputo, Moçambique, 2005.
[26]	Mae, Perfil do Distrito de Funhalouro, Província de Inhambane, Mae, Maputo, Moçambique, 2005.
[27]	Mae, Perfil do Distrito de Mabote, Província de Inhambane, Mae, Maputo, Moçambique, 2005.
[28]	T.M. Magalhães, “Allometric equations for estimating belowground biomass of Androstachys johnsonii Prain”, Carbon Balance and Management, 10:16, 2015.
[29]	T.M. Magalhães, T. Seifert, “Estimation of tree biomass, carbon stocks, and error propagation in mecrusse woodlands”, Open Journal of Forestry vol. 5, pp. 471–488, 2015.
[30]	T.M. Magalhães, T. Seifert, “Biomass modelling of Androstachys johnsonii Prain – a comparison of three methods to enforce additivity”, International Journal of Forestry Research vol. 2015, pp.1–17, 2015.
[31]	T.M. Magalhães, T. Seifert, “Tree component biomass expansion factors and root-to-shoot ratio of Lebombo ironwood: measurement uncertainty”, Carbon Balance and Management 10: 9, 2015.
[32]	T.M. Magalhães, T. Seifert, “Below- and aboveground architecture of Androstachys johnsonii Prain: Topological analysis of the root and shoot systems”, Plant and Soil, 2015. DOI 10.1007/s11104-015-2527-0.
[33]	FAO, FAO Map of World Soil Resources, Italy, Rome, 2003.
[34]	B. R. Parresol, “Additivity of nonlinear biomass equations”, Can. J. For. Res., vol. 31, pp. 865–878, 2001.
[35]	M. A. M. Brasil, R. A. A. Veiga, and J. L. Timoni, “Erros na determinação da densidade básica da madeira”, CERNE, vol. 1, no. 1, pp. 55–57, 1994.
[36]	I. A. Gier, Forest mensuration (fundamentals); International Institute for Aerospace Survey and Earth Sciences (ITC), The Netherlands, p. 20, 21, 1992.
[37]	J. Bunster, Commercial timbers of Mozambique, Technological catalogue, Traforest Lda, Maputo, Mozambique, 2006.
[38]	T. Seifert, and S. Seifert, “Modelling and simulation of tree biomass”, in Bioenergy from Wood: Sustainable Production in the Tropics; T. Seifert, Ed., pp. 42–65, Springer, Managing Forest Ecosystems, vol. 26, 2014.
[39]	S. A. Machado, A. Figueiredo Filho, Dendrometria, Unicentro, Paraná, Brazil, 2005.
[40]	E. W. Johnson, Forest Sampling Desk Reference, CRC Press LLC, Florida, USA, 2000.
[41]	K. Black, B. Tobin, G. Siaz, K. A. Byrne, and B. Osborne, “Allometric regressions for an improved estimate of biomass expansion factors for Ireland based on a Sitka spruce chronosequence”, Irish Forestry, Vol. 61, no. 1, pp. 50–65, 2004.
[42]	M. Segura, M. Kanninen, “Allometric models for tree volume and total aboveground biomass in a tropical humid forest in Costa Rica”, Biotropica, vol. 37, no. 1, pp. 2–8, 2005.
[43]	K. B. F. Kamelarczyk, “Carbon stock assessment and modelling in Zambia: a UN-REDD programme study”, United Nations–Reducing Emissions from Deforestation and Forest Degradation, Zambia, 2009.
[44]	C. R. Sanquetta, A. P. D. Corte, F. Silva, “Biomass expansion factors and root-to-shoot ratio for Pinus in Brazil”, Carbon Balance and Management, vol. 6, pp. 1–8, 2011.
[45]	S. Brown, “Estimating biomass and biomass change of tropical forests: a primer,” FAO Forest Paper 134, 1997.
[46]	A. A. Sitoe, and N. S. Ribeiro, Miombo Book Project (Case Study of Mozambique), Universidade Eduardo Mondlane (UEM). Maputo, Mozambique, 1995.
[47]	R. Mate, T. Johansson, and A. Sitoe, “Biomass equations for Tropical Forest tree species in Mozambique”, Forests, vol. 5, pp. 535-556, 2014.
[48]	N. S. Ribeiro, C. N. Matos, I. R. Moura, R. A. Washington-Allen, and A. I. Ribeiro (2013) “Monitoring vegetation dynamics and carbon stock density in miombo woodlands”, Carbon Balance and Management, vol. 8, no. 1, pp. 1–9, 2014.
[49]	N. Ribeiro, A. A. Sitoe, B. S. Guedes, and C. Staiss, Manual de Silvicultura Tropical, Food and Agriculture Organisation of the United Nations, Maputo, Mozambique, 2002.
[50]	J. Chave, R. Condic, S. Aguilar, A. Hernandez, S. Lao, and R. Perez, “Error propagation and scaling for tropical forest biomass estimates”, Phil. Trans. R. Soc. Lond. B, vol. 309, pp. 409–420, 2004.
[51]	I. F. Brown, L. A. Martinelli, W. W. Thomas, M. Z. Moreira, C. A. C. Ferreira, R. A. Victoria, “Uncertainty in the biomass of Amazonian forests: An example from Rondônia, Brazil”, Forest Ecology and Management, vol. 75, pp. 175–189, 1995.
[52]	D. A. Stellingwerf, Forest inventory and remote sensing, International Training Centre for Aerial Survey (ITC), Enschede, 1994.
[53]	H. B. Stauffer, Some sample size tables for forest sampling, Ministry of Forests, British Columbia, Canada, 1983.

Cite This Article

Plain Text BibTeX RIS

APA Style

Tarquinio Mateus Magalhães, Thomas Seifert. (2015). Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands. American Journal of Agriculture and Forestry, 3(5), 161-170. https://doi.org/10.11648/j.ajaf.20150305.11

Copy | Download

ACS Style

Tarquinio Mateus Magalhães; Thomas Seifert. Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands. Am. J. Agric. For. 2015, 3(5), 161-170. doi: 10.11648/j.ajaf.20150305.11

Copy | Download

AMA Style

Tarquinio Mateus Magalhães, Thomas Seifert. Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands. Am J Agric For. 2015;3(5):161-170. doi: 10.11648/j.ajaf.20150305.11

Copy | Download

@article{10.11648/j.ajaf.20150305.11,
  author = {Tarquinio Mateus Magalhães and Thomas Seifert},
  title = {Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands},
  journal = {American Journal of Agriculture and Forestry},
  volume = {3},
  number = {5},
  pages = {161-170},
  doi = {10.11648/j.ajaf.20150305.11},
  url = {https://doi.org/10.11648/j.ajaf.20150305.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajaf.20150305.11},
  abstract = {Frequently, biomass expansion factors (BEFs), the respective biomass densities, and their uncertainties are computed without taking into account the appropriate estimators. The objective of this study was to compare the estimates of BEF, BEF-based biomass densities, and their uncertainties using different estimators (mean-of-ratios, ratio-of-means, and regression estimators) in double sampling. Our results demonstrated that increased uncertainty is associated with regression-based biomass densities, and that the computation of BEF using merchantable timber volume should utilize regression estimators, not the usual ratio estimators, which preferably, should be avoided altogether, as they are found to be subjective and more susceptible to errors and personal judgment.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands
AU  - Tarquinio Mateus Magalhães
AU  - Thomas Seifert
Y1  - 2015/07/29
PY  - 2015
N1  - https://doi.org/10.11648/j.ajaf.20150305.11
DO  - 10.11648/j.ajaf.20150305.11
T2  - American Journal of Agriculture and Forestry
JF  - American Journal of Agriculture and Forestry
JO  - American Journal of Agriculture and Forestry
SP  - 161
EP  - 170
PB  - Science Publishing Group
SN  - 2330-8591
UR  - https://doi.org/10.11648/j.ajaf.20150305.11
AB  - Frequently, biomass expansion factors (BEFs), the respective biomass densities, and their uncertainties are computed without taking into account the appropriate estimators. The objective of this study was to compare the estimates of BEF, BEF-based biomass densities, and their uncertainties using different estimators (mean-of-ratios, ratio-of-means, and regression estimators) in double sampling. Our results demonstrated that increased uncertainty is associated with regression-based biomass densities, and that the computation of BEF using merchantable timber volume should utilize regression estimators, not the usual ratio estimators, which preferably, should be avoided altogether, as they are found to be subjective and more susceptible to errors and personal judgment.
VL  - 3
IS  - 5
ER  -

Copy | Download

Author Information

Tarquinio Mateus Magalhães
Thomas Seifert

Department of Forest and Wood Science, University of Stellenbosch, Stellenbosch, South Africa

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Tarquinio Mateus Magalhães, Thomas Seifert. (2015). Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands. American Journal of Agriculture and Forestry, 3(5), 161-170. https://doi.org/10.11648/j.ajaf.20150305.11

Copy | Download

ACS Style

Tarquinio Mateus Magalhães; Thomas Seifert. Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands. Am. J. Agric. For. 2015, 3(5), 161-170. doi: 10.11648/j.ajaf.20150305.11

Copy | Download

AMA Style

Tarquinio Mateus Magalhães, Thomas Seifert. Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands. Am J Agric For. 2015;3(5):161-170. doi: 10.11648/j.ajaf.20150305.11

Copy | Download

@article{10.11648/j.ajaf.20150305.11,
  author = {Tarquinio Mateus Magalhães and Thomas Seifert},
  title = {Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands},
  journal = {American Journal of Agriculture and Forestry},
  volume = {3},
  number = {5},
  pages = {161-170},
  doi = {10.11648/j.ajaf.20150305.11},
  url = {https://doi.org/10.11648/j.ajaf.20150305.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajaf.20150305.11},
  abstract = {Frequently, biomass expansion factors (BEFs), the respective biomass densities, and their uncertainties are computed without taking into account the appropriate estimators. The objective of this study was to compare the estimates of BEF, BEF-based biomass densities, and their uncertainties using different estimators (mean-of-ratios, ratio-of-means, and regression estimators) in double sampling. Our results demonstrated that increased uncertainty is associated with regression-based biomass densities, and that the computation of BEF using merchantable timber volume should utilize regression estimators, not the usual ratio estimators, which preferably, should be avoided altogether, as they are found to be subjective and more susceptible to errors and personal judgment.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Estimates of Tree Biomass, and Its Uncertainties Through Mean-of-Ratios, Ratio-of-Means, and Regression Estimators in Double Sampling: A Comparative Study of Mecrusse Woodlands
AU  - Tarquinio Mateus Magalhães
AU  - Thomas Seifert
Y1  - 2015/07/29
PY  - 2015
N1  - https://doi.org/10.11648/j.ajaf.20150305.11
DO  - 10.11648/j.ajaf.20150305.11
T2  - American Journal of Agriculture and Forestry
JF  - American Journal of Agriculture and Forestry
JO  - American Journal of Agriculture and Forestry
SP  - 161
EP  - 170
PB  - Science Publishing Group
SN  - 2330-8591
UR  - https://doi.org/10.11648/j.ajaf.20150305.11
AB  - Frequently, biomass expansion factors (BEFs), the respective biomass densities, and their uncertainties are computed without taking into account the appropriate estimators. The objective of this study was to compare the estimates of BEF, BEF-based biomass densities, and their uncertainties using different estimators (mean-of-ratios, ratio-of-means, and regression estimators) in double sampling. Our results demonstrated that increased uncertainty is associated with regression-based biomass densities, and that the computation of BEF using merchantable timber volume should utilize regression estimators, not the usual ratio estimators, which preferably, should be avoided altogether, as they are found to be subjective and more susceptible to errors and personal judgment.
VL  - 3
IS  - 5
ER  -

Copy | Download