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On Carbon Sequestration Based on Above Ground Biomass (AGB) Modeling of Selected Tree Species in Nigeria

Received: 26 May 2022    Accepted: 4 July 2022    Published: 29 July 2022
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Abstract

Allometric models are important for quantifying biomass and carbon storage in terrestrial ecosystems. Generalized allometry exists for tropical trees but species- and site-specific models are more accurate. This paper is to investigate forest inventory data extracted from the Forestry Research Institute of Nigeria (FRIN) repository to compute the Above Ground Biomass (AGB) for five tree species namely; Terminalia Superba, Bombax Rhodognaphadon, Gmelina Arborea, Mansonia Altissima, Pinus Caribaea, Khaya Senegalensis, Khaya Grandifoliola and Shorea Robusta. Allometric models were used with the least squares’ parameter estimates derived from the Marquardt algorithm to compute the above ground biomass of the five tree species selected. Descriptive Statistics alongside selected methods in inferential and non-parametric statistics such as Runs, Normality (KS & SW), and F-tests were done. Model selection criteria such as AIC, BIC, R2, MSE, MAE and RSE were used to select the most appropriate models for modeling AGB of the selected tree species. Chave. Model (2005) fitted best the computed AGB for Bombax Rhodognaphadon and Terminalia Superba while Brown. Moist model (1989) fitted best the AGB of Gmelina Arborea, Khaya Senegalensis, Khaya Grandifoliola and Mansonia Altissima.

Published in American Journal of Biological and Environmental Statistics (Volume 8, Issue 3)
DOI 10.11648/j.ajbes.20220803.15
Page(s) 81-92
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Above Ground Biomass, Carbon Sequestration, Statistical Modeling, Non-linear Models, Allometric Models

References
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Cite This Article
  • APA Style

    Oluwafemi Samuel Oyamakin, Peter Shina Adebayo. (2022). On Carbon Sequestration Based on Above Ground Biomass (AGB) Modeling of Selected Tree Species in Nigeria. American Journal of Biological and Environmental Statistics, 8(3), 81-92. https://doi.org/10.11648/j.ajbes.20220803.15

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    ACS Style

    Oluwafemi Samuel Oyamakin; Peter Shina Adebayo. On Carbon Sequestration Based on Above Ground Biomass (AGB) Modeling of Selected Tree Species in Nigeria. Am. J. Biol. Environ. Stat. 2022, 8(3), 81-92. doi: 10.11648/j.ajbes.20220803.15

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    AMA Style

    Oluwafemi Samuel Oyamakin, Peter Shina Adebayo. On Carbon Sequestration Based on Above Ground Biomass (AGB) Modeling of Selected Tree Species in Nigeria. Am J Biol Environ Stat. 2022;8(3):81-92. doi: 10.11648/j.ajbes.20220803.15

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  • @article{10.11648/j.ajbes.20220803.15,
      author = {Oluwafemi Samuel Oyamakin and Peter Shina Adebayo},
      title = {On Carbon Sequestration Based on Above Ground Biomass (AGB) Modeling of Selected Tree Species in Nigeria},
      journal = {American Journal of Biological and Environmental Statistics},
      volume = {8},
      number = {3},
      pages = {81-92},
      doi = {10.11648/j.ajbes.20220803.15},
      url = {https://doi.org/10.11648/j.ajbes.20220803.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20220803.15},
      abstract = {Allometric models are important for quantifying biomass and carbon storage in terrestrial ecosystems. Generalized allometry exists for tropical trees but species- and site-specific models are more accurate. This paper is to investigate forest inventory data extracted from the Forestry Research Institute of Nigeria (FRIN) repository to compute the Above Ground Biomass (AGB) for five tree species namely; Terminalia Superba, Bombax Rhodognaphadon, Gmelina Arborea, Mansonia Altissima, Pinus Caribaea, Khaya Senegalensis, Khaya Grandifoliola and Shorea Robusta. Allometric models were used with the least squares’ parameter estimates derived from the Marquardt algorithm to compute the above ground biomass of the five tree species selected. Descriptive Statistics alongside selected methods in inferential and non-parametric statistics such as Runs, Normality (KS & SW), and F-tests were done. Model selection criteria such as AIC, BIC, R2, MSE, MAE and RSE were used to select the most appropriate models for modeling AGB of the selected tree species. Chave. Model (2005) fitted best the computed AGB for Bombax Rhodognaphadon and Terminalia Superba while Brown. Moist model (1989) fitted best the AGB of Gmelina Arborea, Khaya Senegalensis, Khaya Grandifoliola and Mansonia Altissima.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - On Carbon Sequestration Based on Above Ground Biomass (AGB) Modeling of Selected Tree Species in Nigeria
    AU  - Oluwafemi Samuel Oyamakin
    AU  - Peter Shina Adebayo
    Y1  - 2022/07/29
    PY  - 2022
    N1  - https://doi.org/10.11648/j.ajbes.20220803.15
    DO  - 10.11648/j.ajbes.20220803.15
    T2  - American Journal of Biological and Environmental Statistics
    JF  - American Journal of Biological and Environmental Statistics
    JO  - American Journal of Biological and Environmental Statistics
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    EP  - 92
    PB  - Science Publishing Group
    SN  - 2471-979X
    UR  - https://doi.org/10.11648/j.ajbes.20220803.15
    AB  - Allometric models are important for quantifying biomass and carbon storage in terrestrial ecosystems. Generalized allometry exists for tropical trees but species- and site-specific models are more accurate. This paper is to investigate forest inventory data extracted from the Forestry Research Institute of Nigeria (FRIN) repository to compute the Above Ground Biomass (AGB) for five tree species namely; Terminalia Superba, Bombax Rhodognaphadon, Gmelina Arborea, Mansonia Altissima, Pinus Caribaea, Khaya Senegalensis, Khaya Grandifoliola and Shorea Robusta. Allometric models were used with the least squares’ parameter estimates derived from the Marquardt algorithm to compute the above ground biomass of the five tree species selected. Descriptive Statistics alongside selected methods in inferential and non-parametric statistics such as Runs, Normality (KS & SW), and F-tests were done. Model selection criteria such as AIC, BIC, R2, MSE, MAE and RSE were used to select the most appropriate models for modeling AGB of the selected tree species. Chave. Model (2005) fitted best the computed AGB for Bombax Rhodognaphadon and Terminalia Superba while Brown. Moist model (1989) fitted best the AGB of Gmelina Arborea, Khaya Senegalensis, Khaya Grandifoliola and Mansonia Altissima.
    VL  - 8
    IS  - 3
    ER  - 

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Author Information
  • Biostatistics Unit, Department of Statistics, University of Ibadan, Ibadan, Nigeria

  • Biostatistics Unit, Department of Statistics, University of Ibadan, Ibadan, Nigeria

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