New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests,Global Change Biology

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New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests
Global Change Biology ( IF 10.8 ) Pub Date : 2024-08-19 , DOI: 10.1111/gcb.17473
Louise Terryn ₁ , Kim Calders ₁ , Félicien Meunier ₁ , Marijn Bauters _{1,

2} , Pascal Boeckx ₂ , Benjamin Brede ₃ , Andrew Burt ₄ , Jerome Chave ₅ , Antonio Carlos Lola da Costa _{6,

7} , Barbara D'hont ₁ , Mathias Disney _{8,

9} , Tommaso Jucker ₁₀ , Alvaro Lau ₁₁ , Susan G W Laurance ₁₂ , Eduardo Eiji Maeda _{13,

14} , Patrick Meir ₁₅ , Sruthi M Krishna Moorthy _{1,

16} , Matheus Henrique Nunes _{14,

17} , Alexander Shenkin ₁₈ , Thomas Sibret _{1,

2} , Tom E Verhelst ₁ , Phil Wilkes _{19,

20} , Hans Verbeeck ₁

Affiliation

Q-ForestLab, Department of Environment, Ghent University, Ghent, Belgium.
ISOFYS - Isotope Bioscience Laboratory, Department of Green Chemistry and Technology, Ghent University, Ghent, Belgium.
GFZ German Research Centre for Geosciences, Potsdam, Germany.
Sylvera Ltd, London, UK.
Laboratoire Evolution and Biological Diversity (EDB), CNRS/IRD/UPS, Toulouse, France.
Geociencias, Federal University of Para, Belem, State of Para, Brazil.
Museu Paraense Emilio Goeldi, Belem, State of Para, Brazil.
UCL Department of Geography, London, UK.
NERC National Centre for Earth Observation (NCEO-UCL), Swindon, UK.
School of Biological Sciences, University of Bristol, Bristol, UK.
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, Gelderland, the Netherlands.
Centre for Tropical Environmental and Sustainability Science and College of Science and Engineering, James Cook University, Cairns, Australia.
Finnish Meteorological Institute, FMI, Helsinki, Finland.
Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland.
School of Geosciences, University of Edinburgh, Edinburgh, UK.
Department of Biology, University of Oxford, Oxford, UK.
Department of Geographical Sciences, University of Maryland, College Park, Maryland, USA.
School of Informatics, Computing, and Cyber Systems, Northern Arizona University Flagstaff, Flagstaff, Arizona, USA.
Department of Geography, University College London, London, UK.
NERC National Centre for Earth Observation, Leicester, UK.

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 H:D 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 H:D 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 H:D allometries. Additionally, TLS‐based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory‐based H:D 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 H:D 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.

中文翻译：

从地面激光扫描得出的新树高异速生长计揭示了与热带雨林森林清查方法的巨大差异

树木异速生长模型对于监测和预测陆地碳储量至关重要，传统上建立在全球数据库之上，其中包含树干直径（D）和树高（H）的森林清查测量值。然而，这些数据库通常结合了通过各种测量方法获得的 H 测量值，每种方法都有不同的误差模式，从而影响生成的 H：D 异速体。近几十年来，地面激光扫描（TLS）已成为一种被广泛接受的准确、无损树木结构测量方法。本研究使用 TLS 数据来评估基于森林清查的 H：D 异速生长计的预测准确性，并开发更准确的泛热带异速生长计。我们考虑了四大洲的 19 个热带雨林地块。11 个样地具有森林清查和基于 RIEGL VZ-400（i） TLS 的 D 和 H 数据，允许对当地基于森林清查的 H：D 异速生长进行准确性评估。此外，来自所有 19 个样地的 1951 棵树的基于 TLS 的数据被用于为热带雨林创建新的泛热带 H：D 异速生长计。我们的研究结果表明，在大多数样地中，与基于 TLS 的异速生长相比，基于森林清查的 H：D 异速生长低估了 H。对于 30 米高的树木，这些低估从 -1.6 米（-5.3%）到 -7.5 米（-25.4%）不等。在树木高达 77 m 的马来西亚地块中，低估高达 -31.7 m （-41.3%）。我们提出了一种基于 TLS 的泛热带 H：D 异速生长法，将最大气候缺水纳入场地效应，平均不确定性为 19.1%，平均偏差为 -4.8%。而平均不确定性约为 2。该模型比 Chave2014 模型高 3%，在树木大小范围内表现出更一致的不确定性，并且对 H 的估计偏差较小（减少了 8.23%）。总之，从森林清查方法中识别 H 测量的误差至关重要，因为它们可以传播到它们所告知的异速生长中。这项研究强调了 TLS 在热带雨林中准确测量 H 和 D 的潜力，这对于改进树木异速生长至关重要。

更新日期：2024-08-19

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