Evaluation of Stem Biomass and Carbon Density of Four Deciduous Tree Species in Northern Plains of India Using Regression Modeling
Journal Title: Current Journal of Applied Science and Technology - Year 2017, Vol 21, Issue 1
Abstract
Assessment of carbon stock in trees is generally based on allometric equations relating either volume, or biomass, or carbon to DBH. The carbon density of different tree parts is not often measured directly, but generally assumed to be 50% of dry weight. In this study we try to analyze those assumptions and determined the effect different regression equations on carbon sequestration for Tectona grandis, Vachellia nilotica, Madhuca indica, Dalbergia sissoo. The present study aims to estimate the above-ground biomass (AGB) and carbon sequestration in 18 sampling plots of 30 × 30 m2 size, at different sites in northern plains (Uttar Pradesh) India. Two regression models were used for each species; one using DBH only (Method 1) and the other using DBH and height (Method 2). The best fit models were chosen on the basis of highest R2. The DBH, AGB and carbon density yielded a positive relationship for all the species. Apart from Model D1h, all R2 values for models developed with our data (both DBH and height) were above 99%. The R2 values for models developed with DBH only were below 90%, least for model M1 (77.6%) The co-efficient for DBH was not significant in Model D1h and M1h, but the co-efficient for DBH and height was significant at the 5% level of significance for all other coefficients in all other models. The estimated stem AGB was maximum for Tectona grandis with 376.2 and 355.63 t/tree with carbon sequestration of 621.25 and 587.50 kg/ha for the equation T1 and T2H respectively; whereas minimum AGB was recorded for Dalbergia sisoo with 221.55 and 211.58 t/ha and carbon sequestration of 362.93 and 349.65 kg/ha. The AGB and carbon sequestration estimation obtained in this study represents a more realistic picture of biomass of region.
Authors and Affiliations
Naseer A. Mir, P. A. Sofi, Gowher N. Parrey, T. A. Rather, Hilal A. Bhat
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