Applying taper function models for black locust plantations in Greek post-mining areas.
Sci Rep
; 14(1): 13557, 2024 06 12.
Article
em En
| MEDLINE
| ID: mdl-38866843
ABSTRACT
A key process in forest management planning is the estimation of tree volume and, more specifically, merchantable volume. The ability to predict the cumulative stem volume relative to any upper stem diameter on standing trees or stands is essential for forest inventories and the management of forest resources. In the 1980s, the Hellenic Public Power Corporation (HPPC) started the rehabilitation of lignite post-mining areas in Greece by planting mainly black locust (Robinia pseudoacacia, L.). Today, these plantations occupy an area of approximately 2570 ha, but the stem volume has not yet been estimated. Therefore, we aimed to estimate the over- and under-bark stem volume using taper function models for 30 destructively sampled trees. Of the nineteen calibrated fixed-effects models, Kozak's (2004) equation performed best for both the over-bark and under-bark datasets, followed by Lee's (2003) and Muhairwe's (1999) equations. Two fixed effect models were compared with fitted coefficients from Poland and the United States confirming that the local model fits were better suited, as the foreign model coefficients caused an increase in root mean square error (RMSE) for stem diameter predictions of 13% and 218%, respectively. The addition of random effects on a single-stem basis for two coefficients of Kozak's (2004) equation improved the model fit significantly at 86% of the over-bark fixed effect RMSE and 69% for the under-bark model. Integrated taper functions were found to slightly outperform three volume equations for predictions of single stem volume over and under bark. Ultimately it was shown that these models can be used to precisely predict stem diameters and total stem volume for the population average as well as for specific trees of the black locust plantations in the study area.
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MEDLINE
Assunto principal:
Robinia
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article