Open Access Open Access  Restricted Access Subscription Access

A Study on General Allometric Relationships Developed for Biomass Estimation in Regional Scale Taking the Example of Tectona grandis Grown in Bundelkhand Region of India


Affiliations
1 Indian Grassland and Fodder Research Institute, Jhansi 284 003, India
2 Uttar Banga Krishi Viswavidyalaya, Cooch Behar 736 165, India
 

In this communication an effort has been made to develop a general non-site specific allometric relationship taking Tectona grandis grown in semi-arid Bundelkhand region without harvesting any tree. To determine the most appropriate predictor variable for producing the relationship, different physiological parameters of this tree species like diameter at breast height (dbh), basal diameter, tree height, forking height, collar diameter, etc. were collected from the standing trees from MP part of Bundelkhand region, comprising a total of 45 sites of 4 districts namely Guna, Vidisha, Chhatarpur and Tikamgarh. The dataset contained 418 trees with biomass ranging from 12.79 kg/tree to 12707.92 kg/tree, height ranging from 1.5 to 18.5 m and dbh ranging from 0.03 to 0.44 m. For developing the models; dbh, height, dbh × height and dbh2 × height were used as predictor variables. All four contrasting sites were taken for developing allometric models and after examining model residuals and site-specific relationships, it was found that using dbh2 × height alone as the predictor variable produced the most stable model. Thus it makes regional estimation of aboveground biomass production easier with precision as accurate as site-specific allometry.

Keywords

Allometry, Bundelkhand Region, Normalized Difference Vegetation Index, Residual Diagnostics, Tectona grandis.
User
Notifications
Font Size

  • Gould, S. J., Allometry and size in ontogeny and phylogeny. Biol. Rev., 1966, 41, 587–638.
  • Peng, C., Growth and yield models for uneven-aged stands: past, present and future. For. Ecol. Manag., 2000, 132, 259–279.
  • Favrichon, V., Modeling the dynamics and species composition of tropical mixed- species uneven-aged natural forest: effects of alternative cutting regimes. For. Sci., 1998, 44, 113–124.
  • Namaalwa, J., Eid, T. and Sankhayan, P., A multi-species densitydependent matrix growth model for the dry woodlands of Uganda. For. Ecol. Manage., 2005, 213, 312–327.
  • Picard, N., Yalibanda, Y., Namkosserena, S. and Baya, F., Estimating the stock recovery rate using matrix models. For. Ecol. Manage., 2008, 255, 3597–3605.
  • Gourlet-Fleury, S. and Houllier, F., Modelling diameter increment in a lowland evergreen rain forest in French Guiana. For. Ecol. Manage., 2000, 131, 269–289.
  • Crow, T. R., Common regression to estimate tree biomass in tropical stands. For. Sci., 1978, 24, 110–114.
  • Ketterings, Q. M., Richard, C., Yakub, A. and Cheryl, A. P., Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For. Ecol. Manage., 2001, 146, 199–209.
  • Menon, A. R. R. and Thomas, T. P., National carbon project: Spatial assessment of vegetation and soil carbon pool of Northern Kerala, Final report of the project, 2011, p. 13; ISSN 0970-8103.
  • Gertner, G. Z., The sensitivity of measurement error in stand volume estimation. Can. J. For. Res., 1991, 20, 800–804.
  • Zanne, A. E. et al., Global wood density database. Dryad, 2009, identifier (http://hdl.handle.net/10255/dryad.235).
  • Priyanka, B., Chaubey, O. P. and Singhal, P. K., Biomass accumulation and carbon sequestration in Tectona grandis Linn. f. and Gmelina arborea Roxb. Int. J. Bio-Sci. Bio-Technol., 2013, 5, 153–173.
  • Brown, S. and Luge, A. E., Aboveground biomass estimates for tropical moist forests of the Brazilian Amazon. Jaterciercia, 1992, 17, 8–18.
  • Simon, E., Buendia, L., Miwa, K., Ngara, T. and Tanabe, K. (eds), IPCC Guidelines for National Greenhouse Gas Inventories, Institute for Global Environmental Strategies (IGES) for the IPCC, 2006, vol. 1, pp. 4–12; ISBN: 4-88788-032-4.
  • Parresol, B. R., Assessing tree and stand biomass: a review with examples and critical comparisons. For. Sci., 1999, 45, 573–593.
  • Montgomery, D. C., Peck, E. A. and Vining, G. G., Introduction to Linear Regression Analysis, John Wiley & Sons, 2003, 3rd edn.
  • Shapiro, S. S. and Wilk, M. B., An analysis of variance test for normality (complete samples). Biometrika, 1965, 52, 591–611.

Abstract Views: 242

PDF Views: 89




  • A Study on General Allometric Relationships Developed for Biomass Estimation in Regional Scale Taking the Example of Tectona grandis Grown in Bundelkhand Region of India

Abstract Views: 242  |  PDF Views: 89

Authors

D. Deb
Indian Grassland and Fodder Research Institute, Jhansi 284 003, India
A. Ghosh
Uttar Banga Krishi Viswavidyalaya, Cooch Behar 736 165, India
J. P. Singh
Indian Grassland and Fodder Research Institute, Jhansi 284 003, India
R. S. Chaurasia
Indian Grassland and Fodder Research Institute, Jhansi 284 003, India

Abstract


In this communication an effort has been made to develop a general non-site specific allometric relationship taking Tectona grandis grown in semi-arid Bundelkhand region without harvesting any tree. To determine the most appropriate predictor variable for producing the relationship, different physiological parameters of this tree species like diameter at breast height (dbh), basal diameter, tree height, forking height, collar diameter, etc. were collected from the standing trees from MP part of Bundelkhand region, comprising a total of 45 sites of 4 districts namely Guna, Vidisha, Chhatarpur and Tikamgarh. The dataset contained 418 trees with biomass ranging from 12.79 kg/tree to 12707.92 kg/tree, height ranging from 1.5 to 18.5 m and dbh ranging from 0.03 to 0.44 m. For developing the models; dbh, height, dbh × height and dbh2 × height were used as predictor variables. All four contrasting sites were taken for developing allometric models and after examining model residuals and site-specific relationships, it was found that using dbh2 × height alone as the predictor variable produced the most stable model. Thus it makes regional estimation of aboveground biomass production easier with precision as accurate as site-specific allometry.

Keywords


Allometry, Bundelkhand Region, Normalized Difference Vegetation Index, Residual Diagnostics, Tectona grandis.

References





DOI: https://doi.org/10.18520/cs%2Fv110%2Fi3%2F414-419