Single-tree crown shape and crown volume models for Pinus nigra J. F. Arnold in central Italy

Key message

The crown volume of Pinus nigra trees can be modelled as a function of the total crown length and the crown radius at crown base to support forest management practices.


Context The crown volume of trees is rarely considered in forest management practices and is often approximated to a simple cone or paraboloid whose volume can be broadly derived from costly measurements.
Aims We developed two equations to predict single-tree crown volumes for Pinus nigra plantations in Italy based on the analysis of a database with 3578 trees.
Methods Two key crown parameters (total length of the crown and crown radius at crown base) were here modelled using directly measurable mensurational data using Generalise Additive Mixed-effect Model. Afterwards, two functions were then proposed to predict single-tree crown volumes.
Results The fitted models were statistically significant and explaining 57.6% for crown radius at crown base and 87.1% for crown length of the total variance. The power model for single-tree crown volumes calculation showed a mean absolute error around 4.1 m3 for the upper portion of the crown and 12.1 m3 for the lower part for a mean absolute relative error of 12.5% and 32.0% respectively for a global value of 16.4%.
Conclusion Single-tree and stand-level data are fundamental to balance forest management trajectories. The provided functions may be used in external dataset to derive indication on the single-tree or stand-level crown volume to be used as indicators of ground coverage.

Forest management; Silviculture; Forest ecology; Planted forest; Tree modelling

Di Salvatore, U., Marchi, M. & Cantiani, P. Single-tree crown shape and crown volume models for Pinus nigra J. F. Arnold in central Italy. Annals of Forest Science 78, 76 (2021).

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Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Guest Editor: Céline Meredieu

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