Biomass and carbon storage of mangrove associate Barringtonia acutangula stand estimated using drone and non-destructive methods
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Abstract. Pasha GAA, Chairul, Mukhtar E. 2026. Biomass and carbon storage of mangrove associate Barringtonia acutangula stand estimated using drone and non-destructive methods. Asian J For 10 (1): r100138. https://doi.org/10.13057/asianjfor/r100138. Mangrove forests are among the largest carbon-storing forest ecosystems in the world, making them highly important in addressing climate change. However, the capacity for carbon uptake and storage within biomass varies considerably among species. Consequently, carbon storage across habitats is strongly influenced by dominant species and tree density. This study aims to analyze biomass and carbon storage in the stands of mangrove associate species, i.e. Barringtonia acutangula in Tangkas Lake, Jambi, Indonesia. A drone-based method and a non-destructive field survey were employed to collect data on mangrove vegetation. Drone was employed to generate Digital Elevation Model (DEM), Digital Terrain Model (DTM) and Canopy Height Model (CHM) to produce biomass and carbon estimate analyzed using formulas in R-studio. Biomass and carbon estimate from non-destructive field approaches were calculated using allometric equations by inputting DBH and tree height measured in the field. This data was also used to validate CHM and biomass and carbon calculated using drone-based method. The results show that the carbon storage of the B. acutangula stands obtained from the drone-based method and the non-destructive method are relatively similar. The mean biomass using drone-based accros transect was 66.425 tons/ha with the mean carbon storage was 31.219 tonC/ha, whereas the mean biomass estimation from the field survey resulted in 64.966 ton/ha with the mean carbon storage was 30.533 tonC/ha. Based on these results, B. acutangula-dominated stands in Tangkas Lake is included in the medium category implying its significant contribution in climate change mitigation. The findings of this study also suggest the potential application of drone-based methods in estimating above-ground biomass and carbon storage in freshwater mangrove ecosystem.
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