, Volume 69, Issue 4, pp 455-465

Even-aged or uneven-aged modelling approach? A case for Pinus brutia

Purchase on Springer.com

$39.95 / €34.95 / £29.95 *

* Final gross prices may vary according to local VAT.

Get Access

Abstract

Context

The past management of Pinus brutia forests in Lebanon has led to diverse stand structures that cannot be easily classified as even-aged (EA) or uneven-aged (UA). Most stands are between these stand types, and they may be called as “semi-even-aged”. This is a very common characteristic throughout the Mediterranean conifer forests and makes the choice between the EA and UA approaches problematic, in both management and modelling. However, previous research has devoted little attention to the performance of growth and yield models when applied to transitional stand structures.

Aims

The aim of this study was to find the best modelling approach and to recommend equations for simulating the dynamics of the semi-even-aged P. brutia stands of Lebanon on an individual-tree basis.

Methods

Fifty sample plots were measured in Lebanon. Individual-tree growth models were fitted to the whole dataset using either UA or EA modelling approach. Models were also fitted using two sub-samples containing the most EA and the most UA plots. The performance and accuracy of the two modelling approaches were evaluated in all three datasets.

Results

The article provides the first complete growth model for uneven-aged P. brutia stands. The EA sub-models presented better statistical fitting. However, the UA sub-models enabled more accurate predictions of wood production and were almost as good as the EA sub-models when predicting stand dynamics of the EA plots. The EA approach provided poor predictions, and the errors were high when it was applied to UA stands.

Conclusions

In structurally complex stands, the UA modelling approach is to be preferred since it predicts the whole stand dynamics more accurately and enables simulations of a broader range of silvicultural treatments.

Handling Editor:

Eric Rigolot

Contribution of the co-authors

Sergio de-Miguel: design of sampling methods, running data analysis, writing the paper, supervising the work, and coordinating the research project.
Timo Pukkala: design of sampling, running data analysis, writing the paper, and supervising the work.
Nabil Assaf: design of sampling methods, data collection, and supervising the work.
José Antonio Bonet: writing the paper, and supervising the work.