Beyond species means - the intraspecific contribution to global wood density variation.
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Wiley
https://doi.org/10.1111/nph.70860
https://doi.org/10.1111/nph.70860
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Publication status: Published
Funder: Ministry of Business, Innovation and Employment; doi: https://doi.org/10.13039/501100003524
Funder: Instituto Nacional de Pesquisas da Amazônia; doi: https://doi.org/10.13039/501100007188
Funder: Fundação de Amparo à Ciência e Tecnologia de Pernambuco
Funder: Universidad de Panamá
Funder: Fondation pour la Recherche sur la Biodiversite; doi: https://doi.org/10.13039/501100003137
Funder: Smithsonian Tropical Research Institute; doi: https://doi.org/10.13039/100009201
Funder: Natural Sciences and Engineering Research Council of Canada; doi: https://doi.org/10.13039/501100000038
Wood density is central for estimating vegetation carbon storage and a plant functional trait of great ecological and evolutionary importance. However, the global extent of wood density variation is unclear, especially at the intraspecific level. We assembled the most comprehensive wood density collection to date, including 109 626 records from 16 829 plant species across woody life forms and biomes (GWDD v.2, available here: doi: 10.5281/zenodo.16919509). Using the GWDD v.2, we explored the sources of wood density variation within individuals, within species and across environmental gradients. Intraspecific variation accounted for c. 15% of overall wood density variation (SD = 0.068 g cm-3). Variance was 50% smaller in sapwood than heartwood, and 30% smaller in branchwood than trunkwood. Individuals in extreme environments (dry, hot and acidic soils) had higher wood density than conspecifics elsewhere (+0.02 g cm-3, c. 4% of the mean). Intraspecific environmental effects strongly tracked interspecific patterns (r = 0.83) but were 70-80% smaller and varied considerably among taxa. Individual plant wood density was difficult to predict (root mean square error > 0.08 g cm-3; single-measurement R2 = 0.59). We recommend: (1) systematic sampling of multiple individuals and tissues for local applications; and (2) expanded taxonomic coverage combined with integrative models for robust estimates across ecological scales.
Funder: Ministry of Business, Innovation and Employment; doi: https://doi.org/10.13039/501100003524
Funder: Instituto Nacional de Pesquisas da Amazônia; doi: https://doi.org/10.13039/501100007188
Funder: Fundação de Amparo à Ciência e Tecnologia de Pernambuco
Funder: Universidad de Panamá
Funder: Fondation pour la Recherche sur la Biodiversite; doi: https://doi.org/10.13039/501100003137
Funder: Smithsonian Tropical Research Institute; doi: https://doi.org/10.13039/100009201
Funder: Natural Sciences and Engineering Research Council of Canada; doi: https://doi.org/10.13039/501100000038
Wood density is central for estimating vegetation carbon storage and a plant functional trait of great ecological and evolutionary importance. However, the global extent of wood density variation is unclear, especially at the intraspecific level. We assembled the most comprehensive wood density collection to date, including 109 626 records from 16 829 plant species across woody life forms and biomes (GWDD v.2, available here: doi: 10.5281/zenodo.16919509). Using the GWDD v.2, we explored the sources of wood density variation within individuals, within species and across environmental gradients. Intraspecific variation accounted for c. 15% of overall wood density variation (SD = 0.068 g cm-3). Variance was 50% smaller in sapwood than heartwood, and 30% smaller in branchwood than trunkwood. Individuals in extreme environments (dry, hot and acidic soils) had higher wood density than conspecifics elsewhere (+0.02 g cm-3, c. 4% of the mean). Intraspecific environmental effects strongly tracked interspecific patterns (r = 0.83) but were 70-80% smaller and varied considerably among taxa. Individual plant wood density was difficult to predict (root mean square error > 0.08 g cm-3; single-measurement R2 = 0.59). We recommend: (1) systematic sampling of multiple individuals and tissues for local applications; and (2) expanded taxonomic coverage combined with integrative models for robust estimates across ecological scales.