Forecasting the Carbon Sequestration of System of Intensive Forestation at the Wang Chan Forest Learning Center, Rayong Province

Abstract

The research objective was to determine the tree carbon storage and to generate the forecasting carbon sequestration in the next five years of forest planted by System of Intensive Forestation (SIF) at the Wang Chan Forest Learning Center, Rayong Province. Data collection was done from permanent sample plots of size 40x40 m² base on stratified random sampling method by density of trees namely high, medium and low, with one plot per stratum. The data recorded were the tree species, respective diameters, and the total height of every tree in the permanent sample plots from 2015–2022 anuanly. The biomass was estimated using allometric equation specified for dry evergreen forests and the carbon sequestered was quantified by following the methodology of Intergovernmental Panel on Climate Change (IPCC) 2006. The regression equations were used to forecast the carbon dioxide that would be sequestered in the next five years.

 We found 64 tree species, 58 genus, and 33 families. The highest tree density was of Dalbergia cochinchinensis, with Pterocarpus macrocarpus and Lagerstroemia floribunda having the next highest densities, of 19.58, 11.13 and 10.54 tree/rai (122.38, 69.56 and 65.88 tree/ha), respectively, with a biomass of 10.21 ton/rai (63.81 ton/ha). The carbon sequestered for 8 years was estimated at 4.80 tonC/rai (30.00 tonC/ha), while the carbon dioxide sequestered was 17.60 tonCO₂/rai (110.00 tonCO₂/ha), with a increment rate of 2.20 tonCO₂/rai/year (13.75 tonCO₂/ha/year). The regression equation forecasted the amount of carbon dioxide sequestered within the next five years (2023–2027) was of the form; carbon dioxide sequestration = -4.72+(2.63*Year), R² = 0.93. Using this equation, the carbon sequestration of 2023–2027 were 18.95, 21.58, 24.21, 26.84 and 29.47 tonCO₂/rai (118.43, 134.87, 151.31, 167.75 and 184.18 tonCO₂/ha, respectively.