Estimation of Above Ground Tree Biomass and Carbon of Pinus caribaea (Morelet)

• Main Authors: S.M.C.U.P. Subasinghe, G.B. Munasinghe
• Format: Article
• Language: English
• Published: University of Sri Jayewardenepura 2011-10-01
• Series: Journal of Tropical Forestry and Environment
• Subjects: Tree Biomass; Carbon; Pinus caribaea
• Online Access: http://journals.sjp.ac.lk/index.php/JTFE/article/view/85/39

Forests in Sri Lanka contribute to the mitigation of global climate change through sequestrating a net amount of carbon dioxide and also maintaining carbon stocks as forest biomass. This study was conducted using an empirical method to understand the biomass and stored carbon by forest plantations in Sri Lanka. Further, in this study, the possibility of predicting the above ground tree biomass and carbon of Pinus caribaea (Morelet) was investigated. A 27 year old P. caribaea plantation was selected from the Low Country Wet Zone in Sri Lanka and the data were collected using 0.05 ha sample plots. Without felling trees, a core sample was obtained from the stem and biomass and carbon of that sample was used to estimate the stem biomass and carbon through volume measurements. The canopy biomass and carbon were estimated using samples of primary, secondary and tertiary branches and leaves. The total above ground tree biomass and carbon were estimated by adding the stem and canopy values together.It was found that, for 27 year old P. caribaea, the average above ground tree biomass was 368.9 kg and the carbon was 215.9 kg which is 58.5% from the biomass. The amount of carbon in the canopy was 64.5% from the canopy dry mass. The carbon percentages of the primary, secondary and tertiary branches and leaves were 61.7, 59.1 and 79.6 respectively. The total above ground tree carbon for a 27 year old P. caribaea plantation was 103.6 T ha-1. Then regression models were developed to identify the relationships of biomass and carbon with stem volume. A relationship between biomass and carbon was also developed for the selected species. Finally, mathematical models were developed to predict biomass and carbon using some other tree variables such as diameter and height, without felling the trees.