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Yang H, Wang S, Son R, Lee H, Benson V, Zhang W, Zhang Y, Zhang Y, Kattge J, Boenisch G, Schepaschenko D, Karaszewski Z, Stereńczak K, Moreno-Martínez Á, Nabais C, Birnbaum P, Vieilledent G, Weber U, Carvalhais N. Global patterns of tree wood density. Glob Chang Biol 2024; 30:e17224. [PMID: 38459661 DOI: 10.1111/gcb.17224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 02/10/2024] [Accepted: 02/12/2024] [Indexed: 03/10/2024]
Abstract
Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high-resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree-level wood density measurements. An ensemble of four top-performing models combined with eight cross-validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%-63% of spatial variations, followed by vegetation characteristics (25%-31%) and edaphic properties (11%-16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change.
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Affiliation(s)
- Hui Yang
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Siyuan Wang
- Max Planck Institute for Biogeochemistry, Jena, Germany
- Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Dresden, Germany
| | - Rackhun Son
- Max Planck Institute for Biogeochemistry, Jena, Germany
- Department of Environmental Atmospheric Sciences, Pukyong National University, Busan, South Korea
| | - Hoontaek Lee
- Max Planck Institute for Biogeochemistry, Jena, Germany
- Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Dresden, Germany
| | - Vitus Benson
- Max Planck Institute for Biogeochemistry, Jena, Germany
- ELLIS Unit Jena, Jena, Germany
| | - Weijie Zhang
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Yahai Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Yuzhen Zhang
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Jens Kattge
- Max Planck Institute for Biogeochemistry, Jena, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | | | - Dmitry Schepaschenko
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
| | - Zbigniew Karaszewski
- Research Group of Chemical Technology and Environmental Protection, Łukasiewicz Research Network Poznań Institute of Technology Center of Sustainable Economy, Poznań, Poland
| | | | | | - Cristina Nabais
- Centre for Functional Ecology, Associate Laboratory TERRA, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Philippe Birnbaum
- AMAP, Univ Montpellier, CIRAD, CNRS, INRAE, IRD, Montpellier, France
- Institut Agronomique néo-Calédonien (IAC), Nouméa, New Caledonia
| | | | - Ulrich Weber
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Nuno Carvalhais
- Max Planck Institute for Biogeochemistry, Jena, Germany
- ELLIS Unit Jena, Jena, Germany
- Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Caparica, Portugal
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