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Global patterns of tree wood density.
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- Author(s): Yang, Hui1 (AUTHOR) huiyang@bgc‐jena.mpg.de; Wang, Siyuan1,2 (AUTHOR); Son, Rackhun1,3 (AUTHOR); Lee, Hoontaek1,2 (AUTHOR); Benson, Vitus1,4 (AUTHOR); Zhang, Weijie1 (AUTHOR); Zhang, Yahai5 (AUTHOR); Zhang, Yuzhen1 (AUTHOR); Kattge, Jens1,6 (AUTHOR); Boenisch, Gerhard1 (AUTHOR); Schepaschenko, Dmitry7 (AUTHOR); Karaszewski, Zbigniew8 (AUTHOR); Stereńczak, Krzysztof9 (AUTHOR); Moreno‐Martínez, Álvaro10 (AUTHOR); Nabais, Cristina11 (AUTHOR); Birnbaum, Philippe12,13 (AUTHOR); Vieilledent, Ghislain12 (AUTHOR); Weber, Ulrich1 (AUTHOR); Carvalhais, Nuno1,4,14 (AUTHOR) ncarvalhais@bgc‐jena.mpg.de
- Source:
Global Change Biology. Mar2024, Vol. 30 Issue 3, p1-13. 13p.- Subject Terms:
- Source:
- Additional Information
- Subject Terms:
- 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. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Global Change Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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