Skip to main content

Advertisement

Log in

Which option best estimates the above-ground biomass of mangroves of Bangladesh: pantropical or site- and species-specific models?

  • Original Paper
  • Published:
Wetlands Ecology and Management Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Alvarez E, Rodríguez L, Duque A, Saldarriaga J, Cabrera K, de las Salas G, del Valle I, Lema A, Moreno F, Orrego S (2012) Tree above-ground biomass allometries for carbon stocks estimation in the natural forests of Colombia. For Ecol Manag 267:297–308

    Article  Google Scholar 

  • Basuki TM, van Laake PE, Skidmore AK, Hussin YA (2009) Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests. For Ecol Manag 257:1684–1694

    Article  Google Scholar 

  • Brown S (1997) Estimating biomass and biomass change of tropical forests: a primer. FAO Forestry Paper 134, Rome

    Google Scholar 

  • Brown S, Gillespie AJR, Lugo AE (1989) Biomass estimation method for tropical forests with applications to forest inventory data. For Sci 35:881–902

    Google 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, England

  • 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 145:87–99

    Article  CAS  Google 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 (2005b) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecol 145:87–99

    Article  CAS  Google 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):3177–3190

    Article  Google Scholar 

  • Christensen B (1978) Biomass and primary production of Rhizophora apiculata Bl. in a mangrove in southern Thailand. Aquat Bot 4:43–52

    Article  Google Scholar 

  • Clough BF (1992) Primary productivity and growth of mangrove forests. In: Robertson AI, Alongi DM (eds) Tropical mangrove ecosystem, coastal and estuarine studies 41. American Geophysical Union, Washington, DC, pp 225–250

    Chapter  Google Scholar 

  • Clough BF, Dixon P, Dalhaus O (1997) Allometric relationships for estimating biomass in multi-stemmed mangrove tress. Aust J Bot 45:023–1031

    Article  Google Scholar 

  • Das DK, Alam MK (2001) Trees of Bangladesh. Forest Management Branch, Bangladesh Forest Research Institute (BFRI), Chittagong

    Google Scholar 

  • Djomo AN, Ibrahimab A, Saborowskic J, Gravenhorst G (2010) Allometric equations for biomass estimations in Cameroon and pan moist tropical equations including biomass data from Africa. For Ecol Manag 260:1873–1885

    Article  Google Scholar 

  • Donato DC, Ahmed I, Iqbal Z (2011) Carbon assessment report 2009–2010 inventory of the Sundarbans Reserve Forest. Bangladesh Forest Department, Dhaka

    Google 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/85/085

  • 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: 5

  • FD (2010) Integrated resource management plans for the Sundarbans (2010–2020), vol 1. Forest Department, Ministry of Environment and Forests, Dhaka

    Google 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, Khulna

    Google 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, Athens

    Google Scholar 

  • Hussain Z, Acharya G (1994) Mangroves of the Sundarbans, volume two: Bangladesh. IUCN—The World Conservation Union, Dyna Print, Bangkok

    Google Scholar 

  • IPCC (2003) Good practice guidance for land use, land use change and forestry. Institute of Global Environmental Strategies (IGES), Hayama

    Google Scholar 

  • Ketterings QM, Coe R, Noordwijk MV, Amagau Y, Palm CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forest. For Ecol Manag 146:199–209

    Article  Google Scholar 

  • Komiyama A, Poungparn S, Kato S (2005) Common allometric equations for estimating the tree weight of mangroves. J Trop Ecol 21:471–477

    Article  Google Scholar 

  • Komiyama A, Ong JE, Poungparn S (2008) Allometry, biomass, and productivity of mangrove forests: a review. Aquat Bot 89:128–137

    Article  Google 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 Malaysia

  • 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, Dhaka

    Google 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):37–45

    Google Scholar 

  • Mahmood H, Saberi O, Japar Sidik B, Misri K (2008) Net primary productivity of Bruguiera parviflora (Wight & Arn.) dominated mangrove forest at Kuala Selangor, Malaysia. For Ecol Manag 255:179–182

    Article  Google Scholar 

  • Mahmood H, Siddique MRH, Bose A, Limon SH, Saha S, Chowdhury MRK (2012) Allometry, above-ground biomass and nutrient distribution in Ceriops decandra (Griffith) Ding Hou dominated forest types of the Sundarbans mangrove forest, Bangladesh. Wetl Ecol Manag 20:539–548

    Article  Google Scholar 

  • Mahmood H, Siddique MRH, Saha S, Abdullah SMR (2015) Allometric models for biomass, nutrients and carbon stock in Excoecaria agallocha of the Sundarbans, Bangladesh. Wetl Ecol Manag 23:765–774

    Article  CAS  Google Scholar 

  • Mahmood H, Saha C, Abdullah SMR, Saha S, Siddique MRH (2016a) Allometric biomass, nutrient and carbon stock models for Kandelia candel of the Sundarbans, Bangladesh. Trees 30(3):709–717

    Article  CAS  Google Scholar 

  • Mahmood H, Siddique MRH, Akhter M (2016b) A critical review and database of biomass and volume allometric equation for trees and shrubs of Bangladesh. IOP Conference Series. Earth Env Sci 39:012057. https://doi.org/10.1088/1755-1315/39/1/012057

    Article  Google Scholar 

  • Mayer D, Butler D (1993) Statistical validation. Ecol Model 68(1):21–32

    Article  Google Scholar 

  • Nam VT, van Kuijk M, Anten NPR (2016) Allometric equations for aboveground and belowground biomass estimations in an evergreen forest in Vietnam. PLoS ONE 11(6):e0156827. https://doi.org/10.1371/journal.pone.0156827

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nelson BW, Mesquita R, Pereira JLG, Souza SGAD, Batista GT, Couto LB (1999) Allometric regressions for improved estimate of secondary forest biomass in the central Amazon. For Ecol Manag 117:149–167

    Article  Google Scholar 

  • Njana MA, Bollandsås OM, Eid T, Zahabu E, Malimbwi RE (2016a) Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effect modeling approach. Ann For Sci 73:353–369

    Article  Google Scholar 

  • Njana MA, Meilby H, Eid T, Zahabu E, Malimbw RE (2016b) Importance of tree basic density in biomass estimation and associated uncertainties: a case of three mangrove species in Tanzania. Ann For Sci 73(4):1073–1087

    Article  Google Scholar 

  • Peters R, Vovides AG, Luna S, Grüters Uwe, Berger Uta (2014) Changes in allometric relations of mangrove trees due to resource availability–A new mechanistic modelling approach. Ecol Model 283:53–61

    Article  Google 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, Montpellier

    Google Scholar 

  • Piñeiro G, Perelman S, Guerschman JP, Paruelo JM (2008) How to evaluate models: observed vs predicted or predicted vs observed. Ecol Model 216:316–322

    Article  Google Scholar 

  • Ray R, Ganguly D, Chowdhury C, Dey M, Das S, Dutta MK, Mandal SK, Majumder N, De TK, Mukhopadhyay JTK (2011) Carbon sequestration and annual increase of carbon stock in mangrove forest. Atmos Environ 45:5016–5024

    Article  CAS  Google 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, Dhaka

    Google 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, Dhaka

    Google Scholar 

  • Saenger P, Siddiqi NA (1993) Land from the sea: the Mangrove Afforestation Program of Bangladesh. Ocean Coast Manag 20:23–39

    Article  Google Scholar 

  • Saintilan N (1997) Above- and below-ground biomasses of two species of mangrove on the Hawkesbury River estuary, New South Wales. Mar Freshw Res 48:147–152

    Article  CAS  Google Scholar 

  • Sattar MA, Bhattacharjee DK, Kabir MF (1999) Physical and mechanical properties and uses of timbers of Bangladesh. Bangladesh Forest Research Institute, Chittagong

    Google Scholar 

  • Siddiqi NA (2001) Mangrove forestry in Bangladesh. Institute of Forestry & Environmental Science, University of Chittagong, Chittagong

    Google Scholar 

  • Sileshi GW (2014) A critical review of forest biomass estimation models, common mistakes and corrective measures. For Ecol Manag 329:237–254

    Article  Google Scholar 

  • Smith TJIII, Whelan KRT (2006) Development of allometric relations for three mangrove species in South Florida for use in the Greater Everglades Ecosystem restoration. Wetl Ecol Manag 14:409–419

    Article  Google Scholar 

  • Somogyi Z, Cienciala E, Mäkipää R, Muukkonen P, Lehtonen A, Weiss P (2007) Indirect methods of large-scale forest biomass estimation. Eur J For Res 126:197–207

    Article  Google Scholar 

  • Sprugel DG (1983) Correcting for bias in log-transformed allometric equations. Ecology 64(1):209–210

    Article  Google Scholar 

  • Steinke TD, Ward CJ, Rajh A (1995) Forest structure and biomass of mangroves in the Mgeni estuary, South Africa. Hydrobiologia 295:159–166

    Article  Google Scholar 

  • Tamai S, Nakasuga T, Tabuchi R, Ogino K (1986) Standing biomass of mangrove forests in southern Thailand. J Jpn For Soc 68:384–388

    Google Scholar 

  • Tomlinson PB (1986) The botany of Mangroves. Cambridge University Press, Cambridge

    Google Scholar 

  • van Breugel M, Ransijn J, Craven D, Bongers F, Hall JS (2011) Estimating carbon stock in secondary forests: decisions and uncertainties associated with allometric biomass models. For Ecol Manag 262:1648–1657

    Article  Google Scholar 

  • Wagenmakers EJ, Farrell S (2004) AIC model selection using Akaike weights. Psychon Bull Rev 11(1):192–196

    Article  PubMed  Google Scholar 

  • Woodroffe CD (1985) Studies of a mangrove basin, Tuff Crater, New Zealand: I. Mangrove biomass and production of detritus. Estuar Coast Shelf Sci 20(3):265–280

    Article  Google Scholar 

  • Xiao CW, Ceulemans R (2004) Allometric relationships for below- and above-ground biomass of young Scots pines. For Ecol Manag 203:177–186

    Article  Google 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

Download references

Acknowledgements

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.

Funding

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hossain Mahmood.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 63 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mahmood, H., Siddique, M.R.H., Rubaiot Abdullah, S.M. et al. Which option best estimates the above-ground biomass of mangroves of Bangladesh: pantropical or site- and species-specific models?. Wetlands Ecol Manage 27, 553–569 (2019). https://doi.org/10.1007/s11273-019-09677-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11273-019-09677-0

Keywords

Navigation