Which option best estimates the above-ground biomass of mangroves of Bangladesh: pantropical or site- and species-specific models?
Bangladesh has the single largest tract of naturally growing mangrove forest as well as the world’s largest manmade mangrove forest on newly accreted land in coastal areas. These mangrove forests provide significant support to the community as sources of renewable resources, shelter from natural calamities, and carbon sinks. The second nationwide forest inventory is now underway in Bangladesh. Biomass and carbon stock assessment of trees and forests is one of the objectives of this inventory. The present study aims to derive multi-species allometric biomass models for the Sundarbans mangrove forests and species-specific allometric biomass models for planted Sonneratia apetala Buch. Ham in the coastal zone of Bangladesh. A total of 342 individuals from 14 tree species from the Sundarbans and 73 individuals of planted S. apetala from the coastal zone were selected for the development and validation of the allometric model. A semi-destructive method was adopted to estimate the biomass of the sample trees. The best fit multi-species allometric model of Total Above-ground Biomass (TAGB) for the Sundarbans zone was Ln (TAGB) = − 6.7189 + 2.1634 * Ln(D) + 0.3752 * Ln(H) + 0.6895 * Ln(W). Moreover, relatively simple models with only DBH or DBH and H as predictive variables are also recommended for the Sundarbans zone. The best fit species-specific allometric model of TAGB for the planted S. apetala was Ln (TAGB) = − 1.7608 + 2.0077 * Ln(D) + 0.2981 * Ln(H), where D = diameter at breast height in cm, H = total height in m, and W = wood density (kg m−3). The derived best fit allometric models of TAGB for the Sundarbans and planted S. apetala were more efficient in biomass estimation than the frequently used regional and pan-tropical allometric models.
KeywordsAllometry Carbon Coastal afforestation Inventory Sonneratia apetala Sundarbans
We greatly acknowledge the financial support of the Food and Agricultural Organization of the United Nations (FAO) through GCP/BGD/058/USA (LOA Code: FAOBGDLOA 2017-008) to accomplish the field and laboratory work. We would like to thank Sundarbans East and Sundarbans West Forest Divisions, the Bangladesh Forest Department and Forestry and Wood Technology Discipline, Khulna University for their logistic support during the field and laboratory analysis.
We greatly acknowledge the financial support of Food and Agriculture Organization of the United Nations through GCP/BGD/058/USA (LOA Code: FAOBGDLOA 2017-008) to accomplish the field and laboratory work.
- Brown S (1997) Estimating biomass and biomass change of tropical forests: a primer. FAO Forestry Paper 134, RomeGoogle Scholar
- Brown S, Gillespie AJR, Lugo AE (1989) Biomass estimation method for tropical forests with applications to forest inventory data. For Sci 35:881–902Google Scholar
- Chaffey DR, Miller FR, Sandom JH (1985) A forest inventory of the Sundarbans, Bangladesh. Project report 140, Overseas Development Administration, Land Resources Development Centre, EnglandGoogle Scholar
- Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Folster H, Fromard F, Higuchi N, Kira T, Lescure JP, Nelson BW, Ogawa H, Puig H, Riera B, Yamakura T (2005a) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145:87–99CrossRefGoogle Scholar
- Chave J, Réjou-Méchain M, Búrquez A, Chidumayo E, Colgan MS, Delitti WB, Duque A, Eid T, Fearnside PM, Goodman RC, Henry M, Martínez-Yrízar A, Mugasha WA, Muller-Landau HC, Mencuccini M, Nelson BW, Ngomanda A, Nogueira EM, Ortiz-Malavassi E, Pélissier R, Ploton P, Ryan CM, Saldarriaga JG, Vieilledent G (2014) Improved allometric models to estimate the aboveground biomass of tropical trees. Glob Change Biol 10(10):3177–3190CrossRefGoogle Scholar
- Das DK, Alam MK (2001) Trees of Bangladesh. Forest Management Branch, Bangladesh Forest Research Institute (BFRI), ChittagongGoogle Scholar
- Donato DC, Ahmed I, Iqbal Z (2011) Carbon assessment report 2009–2010 inventory of the Sundarbans Reserve Forest. Bangladesh Forest Department, DhakaGoogle Scholar
- Drigo R, Latif MA, Chowdhury JA, Shaheduzzaman M (1987) The maturing mangrove plantations of the coastal afforestation project. Food and Agricultural Organization of the United Nations, FAO/UNDP Project BDG/85/085Google Scholar
- Eamus D, Mcguinness K, Burrows W (2000) Review of allometric relationships for estimating woody biomass for Queens land, the Northern Territory and Western Australia. The national carbon accounting system technical report: 5Google Scholar
- FD (2010) Integrated resource management plans for the Sundarbans (2010–2020), vol 1. Forest Department, Ministry of Environment and Forests, DhakaGoogle Scholar
- FD (2017) Bangladesh tree & forest inventory 2016. http://www.bforest.gov.bd/site/page/8fce3a01-7119-4083-9448-489a6a38a1a5/Bangladesh-Forest-Inventory-. Accessed 21 July 2018
- Forestal (1960) Forest inventory 1958–1959 Sundarbans forest, vol 1. Pakistan Industrial Development Corporation, Khulna Newsprint Mill, KhulnaGoogle Scholar
- Golley BF, Mc Ginnis TJ, Clements GR, Child IG, Duever JM (1975) Mineral cycling in a tropical moist forest ecosystem. University of Georgia Press, AthensGoogle Scholar
- Hussain Z, Acharya G (1994) Mangroves of the Sundarbans, volume two: Bangladesh. IUCN—The World Conservation Union, Dyna Print, BangkokGoogle Scholar
- IPCC (2003) Good practice guidance for land use, land use change and forestry. Institute of Global Environmental Strategies (IGES), HayamaGoogle Scholar
- Mahmood H (2004) Biomass, litter production and selected nutrients in Bruguiera Parviflora (Roxb.) Wight & Arn. Dominated Mangrove Forest Ecosystem at Kuala Selangor, Malaysia. Dissertation, University Putra MalaysiaGoogle Scholar
- Mahmood H (2015) Handbook of selected plant species of the Sundarbans and the embankment ecosystem. Sustainable Development and Biodiversity Conservation in Coastal Protection Forests, Bangladesh (SDBC-Sundarbans), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, DhakaGoogle Scholar
- Mahmood H, Saberi O, Japar Sidik B, Misri K, Rajagopal S (2004) Allometric relationships for estimating above and below-ground biomass of saplings and trees of Bruguiera parviflora (Wight and Arnold). Malays Appl Biol 33(1):37–45Google Scholar
- Picard N, Saint-André L, Henry M (2012) Manual for building tree volume and biomass allometric equations: from field measurement to prediction. Food and Agricultural Organization of the United Nations, and Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Montpellier, Rome, MontpellierGoogle Scholar
- Revilla JAV, Ahmed IU, Hossain A (1998a) Forest inventory of the Sundarbans Reserved Forest, final report, vol 1. Mandala Agricultural Development Corporation and Forest Department, Ministry of Environment and Forests, DhakaGoogle Scholar
- Revilla JAV, Ahmed IU, Hossain A (1998b) Coastal plantations of coastal districts of Bangladesh. Final report. Mandala Agricultural Development Corporation and Forest Department, Ministry of Environment and Forests, DhakaGoogle Scholar
- Sattar MA, Bhattacharjee DK, Kabir MF (1999) Physical and mechanical properties and uses of timbers of Bangladesh. Bangladesh Forest Research Institute, ChittagongGoogle Scholar
- Siddiqi NA (2001) Mangrove forestry in Bangladesh. Institute of Forestry & Environmental Science, University of Chittagong, ChittagongGoogle Scholar
- Tamai S, Nakasuga T, Tabuchi R, Ogino K (1986) Standing biomass of mangrove forests in southern Thailand. J Jpn For Soc 68:384–388Google Scholar
- Tomlinson PB (1986) The botany of Mangroves. Cambridge University Press, CambridgeGoogle Scholar
- Zanne AE, Lopez-Gonzalez G, Coomes DA, Ilic J, Jansen S, Lewis SL, Miller RB, Swenson NG, Wiemann MC, Chave J (2009) Global wood density database. Dryad. Identifier: http://hdl.handle.net/10255/dryad.235. Accessed 10 June 2018