3 research outputs found
Pantropical variability in tree crown allometry
Aim:
Tree crowns determine light interception, carbon and water exchange. Thus, understanding the factors causing tree crown allometry to vary at the tree and stand level matters greatly for the development of future vegetation modelling and for the calibration of remote sensing products. Nevertheless, we know little about largeāscale variation and determinants in tropical tree crown allometry. In this study, we explored the continental variation in scaling exponents of siteāspecific crown allometry and assessed their relationships with environmental and standālevel variables in the tropics. /
Location:
Global tropics. /
Time period:
Early 21st century. /
Major taxa studied:
Woody plants. /
Methods:
Using a dataset of 87,737 trees distributed among 245 forest and savanna sites across the tropics, we fitted siteāspecific allometric relationships between crown dimensions (crown depth, diameter and volume) and stem diameter using powerālaw models. Standālevel and environmental drivers of crown allometric relationships were assessed at pantropical and continental scales. /
Results:
The scaling exponents of allometric relationships between stem diameter and crown dimensions were higher in savannas than in forests. We identified that continental crown models were better than pantropical crown models and that continental differences in crown allometric relationships were driven by both standālevel (wood density) and environmental (precipitation, cation exchange capacity and soil texture) variables for both tropical biomes. For a given diameter, forest trees from Asia and savanna trees from Australia had smaller crown dimensions than trees in Africa and America, with crown volumes for some Asian forest trees being smaller than those of trees in African forests. /
Main conclusions:
Our results provide new insight into geographical variability, with large continental differences in tropical tree crown allometry that were driven by standālevel and environmental variables. They have implications for the assessment of ecosystem function and for the monitoring of woody biomass by remote sensing techniques in the global tropics