Modelling above ground biomass accumulation of mangrove plantations in Vietnam

Abstract

In many tropical nations, mangrove forests are essential ecosystems for climate change mitigation and adaptation in coastal regions as they provide important forest resources as well as a suite of other benefits to communities including carbon sequestration. Empirical growth and yield modelling methods derived from terrestrial forestry, which are often robust with respect to forestry forecasting and management, have not often been assessed in mangrove forests yet they are important for underpinning sustainable forest management. We surveyed 89 Rhizophora apiculata mangrove plantations with age ranges from 4 to 26 year old in Vietnam, destructively harvesting 25 trees for biomass measurements and 70 for stem analyses, to assess increments in biomass and standing timber. Systems of equations were developed to model site index, mean diameter, dominant height, stocking, biomass and timber volume. We found that conventional forest growth modelling methods fitted the observed data well. Similar to terrestrial forests, stand height is a good indicator of site productivity. Mean errors for stand volume and biomass estimated from yield tables were both less than 5.3%. The root mean square error (RMSE) of the biomass model was 12 and RMSE of the volume model was 10.8, suggesting that these methods are applicable to evenly aged monoculture mangrove plantations in Vietnam. Our research also indicated high variation in mean annual increment of biomass (MAI) in the surveyed plantations due to a wide range of age and site conditions. Some R. apiculata plantations in Vietnam can reach a peak aboveground biomass MAI of 22.7 Mg ha−1 year−1, which is among the highest of published values from plantations of the same species worldwide. Further studies addressing the application of terrestrial forest growth methods to mangrove systems are suggested in order to develop reliable and useful tools for sustainable management of this important ecosystem.