Articles | Volume 22, issue 5
https://doi.org/10.5194/bg-22-1413-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-1413-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Mar 2025
Research article |
| 13 Mar 2025
| 13 Mar 2025
Selecting allometric equations to estimate forest biomass from plot- rather than individual-level predictive performance
Nicolas Picard
CORRESPONDING AUTHOR
GIP Ecofor, Paris, France
Noël Fonton
Faculty of Agronomic Science, University of Abomey-Calavi, Cotonou, Benin
Faustin Boyemba Bosela
Faculty of Science, University of Kisangani, Kisangani, Democratic Republic of the Congo
Adeline Fayolle
Forêts et Sociétés, Université de Montpellier, Cirad Montpellier, France
Cirad Forêts et Sociétés, Montpellier, France
Joël Loumeto
Faculty of Science and Technology, University Marien NGouabi, Brazzaville, Republic of the Congo
Gabriel Ngua Ayecaba
Instituto Nacional de Desarrollo Forestal y Manejo del Sistema Nacional de Areas Protegidas (INDEFOR), Bata, Equatorial Guinea
Bonaventure Sonké
École normale supérieure, University of Yaoundé 1, Yaounde, Cameroon
Olga Diane Yongo Bombo
Faculty of Science, University of Bangui, Bangui, Central African Republic
Hervé Martial Maïdou
Commission des Forêts d'Afrique Centrale (COMIFAC), Yaounde, Cameroon
Alfred Ngomanda
Centre National de la Recherche Scientifique et Technologique (CENAREST), Libreville, Gabon
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Cited
13 citations as recorded by crossref.
- Predicting individual tree diameter at breast height for genetically diverse Catalpa bungei using nonlinear mixed-effects models and UAV LiDAR data Y. Zhang et al. https://doi.org/10.3389/fpls.2025.1716546
- Biomass models, allometric relationships, and carbon sink of Sargassum henslowianum in Nan'ao Island J. Chen et al. https://doi.org/10.1016/j.rsma.2026.104898
- The effect of fire regimes on above-ground biomass change in Baikiaea-dominated woodlands of the Chobe region, northern Botswana, 1991 – 2023 O. Lekoko et al. https://doi.org/10.1016/j.jenvman.2026.131030
- A Structural Variable-Driven Forest Aboveground Biomass Retrieval Approach Integrating Hybrid Expert Attention and Ecological Priors M. Hao et al. https://doi.org/10.1109/JSTARS.2026.3728487
- Enhancing stem volume estimation for savanna species using variable-exponent taper equation and close-range photogrammetry F. Laly et al. https://doi.org/10.1016/j.fecs.2025.100331
- Allometric equations for orchard and vineyard trees: enhancing AFOLU-based climate change mitigation M. Kwak et al. https://doi.org/10.3389/fpls.2025.1663283
- Quantifying tree biomass: insights from a long-term study at Hubbard Brook Experimental Forest K. Rutherford et al. https://doi.org/10.1139/cjfr-2025-0167
- Derivation and Application of Allometric Equations to Quantify the Net Primary Productivity (NPP) of the Salix pierotii Miq. Community as a Representative Riparian Vegetation Type B. Lim et al. https://doi.org/10.3390/f16081225
- Integrating dendrometric traits and wood density to predict biomass productivity, bioenergy yield, and carbon sequestration in hybrid Populus clones Y. Alkuddsi et al. https://doi.org/10.1038/s41598-026-61798-8
- Modeling forest aboveground biomass in cloud-prone tropical mountains using temporally encoded Sentinel-2 time series and synthetic training data T. Doan et al. https://doi.org/10.1007/s40808-026-02859-9
- Forests as Living Public Infrastructure: Evidence Requirements for Mediterranean Wildfire Risk Governance, Restoration and Carbon Accounting E. Milios & K. Kitikidou https://doi.org/10.3390/sci8080192
- Development of Species-Specific Allometric Models for Aboveground Woody Biomass Estimation of Urban Trees Using Terrestrial Laser Scanning X. Zhang et al. https://doi.org/10.3390/f17091067
- Estimating Pinus taeda (L.) (Loblolly Pine) timber volume with multi-temporal SAR-optical fusion and supervised learning techniques G. Barua et al. https://doi.org/10.1080/01431161.2026.2735047
13 citations as recorded by crossref.
- Predicting individual tree diameter at breast height for genetically diverse Catalpa bungei using nonlinear mixed-effects models and UAV LiDAR data Y. Zhang et al. https://doi.org/10.3389/fpls.2025.1716546
- Biomass models, allometric relationships, and carbon sink of Sargassum henslowianum in Nan'ao Island J. Chen et al. https://doi.org/10.1016/j.rsma.2026.104898
- The effect of fire regimes on above-ground biomass change in Baikiaea-dominated woodlands of the Chobe region, northern Botswana, 1991 – 2023 O. Lekoko et al. https://doi.org/10.1016/j.jenvman.2026.131030
- A Structural Variable-Driven Forest Aboveground Biomass Retrieval Approach Integrating Hybrid Expert Attention and Ecological Priors M. Hao et al. https://doi.org/10.1109/JSTARS.2026.3728487
- Enhancing stem volume estimation for savanna species using variable-exponent taper equation and close-range photogrammetry F. Laly et al. https://doi.org/10.1016/j.fecs.2025.100331
- Allometric equations for orchard and vineyard trees: enhancing AFOLU-based climate change mitigation M. Kwak et al. https://doi.org/10.3389/fpls.2025.1663283
- Quantifying tree biomass: insights from a long-term study at Hubbard Brook Experimental Forest K. Rutherford et al. https://doi.org/10.1139/cjfr-2025-0167
- Derivation and Application of Allometric Equations to Quantify the Net Primary Productivity (NPP) of the Salix pierotii Miq. Community as a Representative Riparian Vegetation Type B. Lim et al. https://doi.org/10.3390/f16081225
- Integrating dendrometric traits and wood density to predict biomass productivity, bioenergy yield, and carbon sequestration in hybrid Populus clones Y. Alkuddsi et al. https://doi.org/10.1038/s41598-026-61798-8
- Modeling forest aboveground biomass in cloud-prone tropical mountains using temporally encoded Sentinel-2 time series and synthetic training data T. Doan et al. https://doi.org/10.1007/s40808-026-02859-9
- Forests as Living Public Infrastructure: Evidence Requirements for Mediterranean Wildfire Risk Governance, Restoration and Carbon Accounting E. Milios & K. Kitikidou https://doi.org/10.3390/sci8080192
- Development of Species-Specific Allometric Models for Aboveground Woody Biomass Estimation of Urban Trees Using Terrestrial Laser Scanning X. Zhang et al. https://doi.org/10.3390/f17091067
- Estimating Pinus taeda (L.) (Loblolly Pine) timber volume with multi-temporal SAR-optical fusion and supervised learning techniques G. Barua et al. https://doi.org/10.1080/01431161.2026.2735047
Saved (final revised paper)
Latest update: 04 Nov 2026
Short summary
Allometric equations predict tree biomass and are crucial for estimating forest carbon storage, thus assessing the role of forests in climate change mitigation. Usually, these equations are selected based on tree-level predictive performance. However, we evaluated the model performance at plot and forest levels, finding it varies with plot size. This has significant implications for reducing uncertainty in biomass estimates at these levels.
Allometric equations predict tree biomass and are crucial for estimating forest carbon storage,...
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