Work

Modelling conductive sapwood area of Gmelina arborea trees grown in the tropical dry forest of Colombia

Year: 2025
Type: article
Abstract: Quantifying tree water use is crucial for developing adaptive forest management strategies to address water scarcity. Transpiration, the major component of tree water consumption, is estimated using stem sap flow velocity and scaled to the conductive sapwood area (S A ). As a vital trait for understanding forest hydrology, S A provides insights into hydraulic functionality and water use. This study examined the dimensions (depth and area) and some wood properties (density and moisture content) of the sapwood in Gmelina arborea trees from tropical dry forests. Non-destructive sampling was conducted on 133 trees across seven stands, aged 4 to 13 years, with site indices ranging from 17.3 to 27.3 m and stand density ranging from 355 to 1750 trees ha –1 . Measurements included diameter at breast height (DBH) and crown projection area (CPA). Sapwood cores were extracted from four cardinal directions to assess sapwood dimensions and wood properties. Tree- and stand-level variation were the primary sources of variation in sapwood dimensions and properties, while within-tree variation influenced sapwood depth and properties but was negligible for S A . No significant effect of cardinal direction on sapwood dimensions or properties was observed, suggesting a uniform radial distribution. Strong correlations were found between S A and DBH and CPA. Allometric models using DBH and CPA predicted S A with high accuracy (R 2 = 0.91 and 0.63), improving further with site index inclusion (R 2 = 0.93 and 0.67). The developed S A models are vital tools for enhancing adaptive forest management, optimizing resource use efficiency, and promoting sustainability in dry climates, providing valuable insights into tree water transport dynamics.
Source: New Forests
Authors: Ana Milena López-Aguirre, Alonso Barrios-Trilleras
Language: English
Open Access status: hybrid
Estimated APC paid: $3,790
OpenAlex ID: W4417022947
FWCI:
Cites: 71
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