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New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests.
Terryn, Louise; Calders, Kim; Meunier, Félicien; Bauters, Marijn; Boeckx, Pascal; Brede, Benjamin; Burt, Andrew; Chave, Jerome; da Costa, Antonio Carlos Lola; D'hont, Barbara; Disney, Mathias; Jucker, Tommaso; Lau, Alvaro; Laurance, Susan G W; Maeda, Eduardo Eiji; Meir, Patrick; Krishna Moorthy, Sruthi M; Nunes, Matheus Henrique; Shenkin, Alexander; Sibret, Thomas; Verhelst, Tom E; Wilkes, Phil; Verbeeck, Hans.
Afiliación
  • Terryn L; Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
  • Calders K; Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
  • Meunier F; Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
  • Bauters M; Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
  • Boeckx P; ISOFYS - Isotope Bioscience Laboratory, Department of Green Chemistry and Technology, Ghent University, Ghent, Belgium.
  • Brede B; ISOFYS - Isotope Bioscience Laboratory, Department of Green Chemistry and Technology, Ghent University, Ghent, Belgium.
  • Burt A; GFZ German Research Centre for Geosciences, Potsdam, Germany.
  • Chave J; Sylvera Ltd, London, UK.
  • da Costa ACL; Laboratoire Evolution and Biological Diversity (EDB), CNRS/IRD/UPS, Toulouse, France.
  • D'hont B; Geociencias, Federal University of Para, Belem, State of Para, Brazil.
  • Disney M; Museu Paraense Emilio Goeldi, Belem, State of Para, Brazil.
  • Jucker T; Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
  • Lau A; UCL Department of Geography, London, UK.
  • Laurance SGW; NERC National Centre for Earth Observation (NCEO-UCL), Swindon, UK.
  • Maeda EE; School of Biological Sciences, University of Bristol, Bristol, UK.
  • Meir P; Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, Gelderland, the Netherlands.
  • Krishna Moorthy SM; Centre for Tropical Environmental and Sustainability Science and College of Science and Engineering, James Cook University, Cairns, Australia.
  • Nunes MH; Finnish Meteorological Institute, FMI, Helsinki, Finland.
  • Shenkin A; Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland.
  • Sibret T; School of Geosciences, University of Edinburgh, Edinburgh, UK.
  • Verhelst TE; Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
  • Wilkes P; Department of Biology, University of Oxford, Oxford, UK.
  • Verbeeck H; Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland.
Glob Chang Biol ; 30(8): e17473, 2024 Aug.
Article en En | MEDLINE | ID: mdl-39155688
ABSTRACT
Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting HD allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based HD allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based HD allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical HD allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based HD allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from -1.6 m (-5.3%) to -7.5 m (-25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as -31.7 m (-41.3%). We propose a TLS-based pantropical HD allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of -4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Árboles / Clima Tropical / Bosque Lluvioso Idioma: En Revista: Glob Chang Biol Año: 2024 Tipo del documento: Article País de afiliación: Bélgica

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Árboles / Clima Tropical / Bosque Lluvioso Idioma: En Revista: Glob Chang Biol Año: 2024 Tipo del documento: Article País de afiliación: Bélgica