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Wetlands Ecology and Management

, Volume 27, Issue 4, pp 553–569 | Cite as

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

  • Hossain MahmoodEmail author
  • Mohammad Raqibul Hasan Siddique
  • S. M. Rubaiot Abdullah
  • Liam Costello
  • Henry Matieu
  • Md. Zaheer Iqbal
  • Mariam Akhter
Original Paper

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.

Keywords

Allometry Carbon Coastal afforestation Inventory Sonneratia apetala Sundarbans 

Notes

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.

Supplementary material

11273_2019_9677_MOESM1_ESM.docx (63 kb)
Supplementary material 1 (DOCX 63 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Forestry and Wood Technology DisciplineKhulna UniversityKhulnaBangladesh
  2. 2.School of Ecosystem and Forest SciencesThe University of MelbourneParkvilleAustralia
  3. 3.Food and Agriculture OrganizationRomeItaly
  4. 4.Bangladesh Forest DepartmentDhakaBangladesh

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