Allometric models for biomass prediction of Hevea brasilliensis

Abstract

AbstractTrees contribute to combating global warming by absorbing CO2, thus enhancing the quality of the environment. Sri Lanka maintains about 112,000 ha of Hevea brasiliensis (rubber) plantations, where 85.7% is in the wet zone. When rubber trees decline in latex production, after 30–33 years of planting, they are harvested to regenerate the next cycle. Rubber timber in Sri Lanka is used mainly for manufacturing interior parts of furniture, tool handles, and toys, leaving minimal chances for the emission of CO2 by combustion. Therefore, rubber is a good source of carbon sequestration, which can be used to earn additional benefits for the farmers. Estimating tree biomass helps to assess the carbon sequestration of those trees. Therefore this study aimed to build allometric models to predict the biomass using diameter at breast height (dbh) and total tree height (h). Since uprooting rubber trees is not allowed till maturity, whole‐tree, above‐ground, and stem biomass prediction models were built by uprooting ten 30‐ and 31‐year‐old trees from two rubber estates of the low country wet zone of Sri Lanka. For the rest of the ages, dbh and h prediction models were built by age using data collected from six age classes of rubber trees from the same two estates so those variables could be used as inputs to the biomass prediction models. For dbh and h models, Michaelis–Menten functions performed better than power‐law functions. Biomass was estimated for the stem and large branches by converting respective volumes to weights. Weight measurements were taken directly for biomass assessment for small branches, foliage, and roots. The quality of models was determined based on both qualitative and quantitative evaluations. The finding proved that the biomass of rubber plantations could effectively be estimated by dbh and h over time.