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

Mo, Lidong; Crowther, Thomas W.; Maynard, Daniel S.; van den Hoogen, Johan; Ma, Haozhi; Bialic-Murphy, Lalasia; Liang, Jingjing; de-Miguel, Sergio; Nabuurs, Gert-Jan; Reich, Peter B.; Phillips, Oliver L.; Abegg, Meinrad; Adou Yao, Yves C.; Alberti, Giorgio; Almeyda Zambrano, Angelica M.; Alvarado, Braulio Vilchez; Alvarez-Dávila, Esteban; Alvarez-Loayza, Patricia; Alves, Luciana F.; ... mehr

Abstract:

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. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000176457
Veröffentlicht am 20.11.2024
Originalveröffentlichung
DOI: 10.1038/s41559-024-02564-9
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Geographie und Geoökologie (IFGG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2397-334X
KITopen-ID: 1000176457
Erschienen in Nature Ecology & Evolution
Verlag Nature Research
Vorab online veröffentlicht am 15.10.2024
Schlagwörter Ecological modelling, Forest ecology, Plant ecology
Nachgewiesen in Scopus
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