Abstract:
Non-destructive methods for estimating carbon storage capacity are becoming increasingly popular as they do not harm the individual trees or the ecosystem. However, currently the destructive method of sampling trees for estimating their carbon storage capacity is widely practiced throughout the world. Therefore, the present study was conducted in a mangrove conservation forest located in a tropical island, Sri Lanka, with the objective of developing allometric equations to predict the stem carbon content of Lumnitzera racemosa and Avicennia marina using non-destructive method of sampling. The allometric model developed for Lumnitzera racemosa from this study, to determine stem carbon content is: Ln C -3.485+ 1.155 Ln SH + 1.892 Ln DBH, Where, C: Stem carbon content, SH: merchantable stem height, DBH: Diameter at breast height. For A. marina, only diameter at breast height was statistically significant with stem carbon content and the allometric equation was, Ln C -3.483 2.407 Ln DBH. The models were evaluated using p value, R value, residual diagram, model bias values and model efficiency values. The models were validated by calculating residual values as the difference between the actual stem carbon content and predicted stem carbon content from the models for Lumniæera racemosa and A. marina. Further, there was no significant difference between the mean values of the measured stem carbon content and the predicted stem carbon content using the prediction models. The results indicate that the developed allometric equations in the present study are practically applicable in the field to estimate the stem carbon content of Lumnitzera racemosa and A. marina. Further, these estimations can contribute to make more accurate valuations on carbon stocks of sequestered carbon necessary for carbon trading purposes and sustainable management of mangrove forest ecosystems.
