Photosynthetic traits scale linearly with relative height within the canopy in an African tropical forest
2025
Sibret, Thomas | Peaucelle, Marc | Crous, Kristine | Meunier, Félicien | Bauters, Marijn | Ellsworth, David | Janssens, Ivan | Boeckx, Pascal | Verbeeck, Hans | Universiteit Gent = Ghent University = Université de Gand (UGENT) | Interactions Sol Plante Atmosphère (UMR ISPA) ; Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Western Sydney University | University of Antwerp (UA)
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Показать больше [+] Меньше [-]Английский. Understanding leaf photosynthetic traits and their variation in tropical forests is crucial for improving model predictions of forest productivity, and accurately representing the high functional diversity in these forests remains a challenge. Moreover, leaf photosynthesis data are lacking for the tropical forest of the Congo basin. We observed photosynthetic, chemical and structural leaf traits of 24 woody species in a Congolese tropical forest and studied their variance across functional guilds, within‐tree crown positions and overall canopy positions defined by their relative height within the canopy. Guild and crown position jointly influenced leaf traits, with a significant effect observed (marginal R 2 > 0.43). The traditional guild classification explained a significant portion of the observed interspecies variation, revealing a clear gradient from shade‐tolerant to light‐demanding species. Crown position significantly affected intraindividual leaf trait variability, with bottom crown leaves exhibiting trait values at least 19.3% lower than top leaves. Importantly, the linear relationship between relative canopy height and leaf traits emerged as a robust and continuous metric, effectively integrating both inter‐ and intraspecific variability. We conclude that while guild‐based classifications provide a useful framework for identifying plant functional groups, relative canopy height offers a robust and quantitative approach for capturing overall canopy trait variation, valuable for modeling canopy processes.
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