The global distribution and drivers of wood density and their impact on forest carbon stocks

环境科学 分布(数学) 生态学 碳储量 林业 碳纤维 气候变化 地理 生物 数学 算法 复合数 数学分析
作者
Lidong Mo,Thomas W. Crowther,Daniel S. Maynard,Johan van den Hoogen,Haozhi Ma,Lalasia Bialic‐Murphy,Jingjing Liang,Sergio de‐Miguel,G.J. Nabuurs,Peter B. Reich,Oliver L. Phillips,Meinrad Abegg,Constant Yves Adou Yao,Giorgio Alberti,Angélica M. Almeyda Zambrano,Braulio Vílchez Alvarado,Esteban Álvarez‐Dávila,Patricia Álvarez-Loayza,Luciana F. Alves,Iêda Leão do Amaral
出处
期刊:Nature Ecology and Evolution [Nature Portfolio]
卷期号:8 (12): 2195-2212 被引量:22
标识
DOI:10.1038/s41559-024-02564-9
摘要

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.
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