Allometric models and aboveground biomass of Lumnitzera racemosa Willd. forest in Rawa Aopa Watumohai National Park, Southeast Sulawesi, Indonesia. Issue 1 (2nd January 2016)

• Record Type: Journal Article
• Authors: Kangkuso, Analuddin; Jamili, Jamili; Septiana, Andi; Raya, Rasas; Sahidin, Idin; Rianse, Usman; Rahim, Saban; Alfirman, Alfirman; Sharma, Sahadev; Nadaoka, Kazuo
• Is Part Of: Forest science and technology. Volume 12:Issue 1(2016)
• Page Start: 43
• Page End: 50
• Publication Date: 2016-01-02
• Subjects: allometric model -- aboveground biomass -- Lumnitzera racemosa -- RAWN Park -- Indonesia; Forests and forestry -- Periodicals; Forests and forestry -- Korea (South) -- Periodicals; Forests and forestry -- Research -- Periodicals; Forests and forestry; Forests and forestry -- Research; Korea (South); Periodicals; 634.9
• DOI: 10.1080/21580103.2015.1034191
• Languages: English
• ISSNs: 2158-0103

Abstract

Abstract : Information on aboveground biomass of mangrove forest at Rawa Aopa Watumohai National (RAWN) Park is fundamental for the management of mangroves ( Lumnitzera racemosa Willd.) in the park. Allometric relationships of partial or whole L. racemosa trees were examined using independent variables D30, DBH, and DB or quadratics D30 2 H, DBH 2 H, and DB 2 H from different individuals of L. racemosa trees. Aboveground biomass was estimated by allometric equations and tree census data. Results showed that the best fit for allometric models of stem biomass (WS) and leaf biomass (WL) used the independent variable of DBH 2 H, while the best fit for branch biomass (WB) used quadratic DB 2 H. The quadratic DBH 2 H is the most reliable parameter for estimating aboveground biomass of L. racemosa trees. Aboveground biomass of L. racemosa varied among stands, ranging from 26.23 to 191.01 ton ha −1 . Biomass density of L. racemosa forest varied from 4.07 to 29.80 ton ha −1 m −1 . The high aboveground biomass of L. racemosa indicates its high blue carbon stock, which maintains the productivity of nearby coastal areas. Therefore, the results of this study can help the sustainable management of mangroves in the RAWN Park and surrounding areas.