Predicting and Mapping Dominant Height of Oriental Beech Stands Using Environmental Variables in Sinop, Northern Turkey

Ismet Yener () and Engin Guvendi
Additional contact information
Ismet Yener: Department of Forest Engineering, Faculty of Forestry, Artvin Coruh University, Artvin 08100, Turkey
Engin Guvendi: Department of Forestry, Kürtün Vocational School, Gümüşhane University, Gümüşhane 29810, Turkey

Sustainability, 2023, vol. 15, issue 19, 1-20

Abstract: The dominant height of forest stands (SDH) is an essential indicator of site productivity in operational forest management. It refers to the capacity of a particular site to support stand growth. Sites with taller dominant trees are typically more productive and may be more suitable for certain management practices. The present study investigated the relationship between the dominant height of oriental beech stands and numerous environmental variables, including physiographic, climatic, and edaphic attributes. We developed models and generated maps of SDH using multilinear regression (MLR) and regression tree (RT) techniques based on environmental variables. With this aim, the total height, diameter at breast height, and age of sample trees were measured on 222 sample plots. Additionally, topsoil samples (0–20 cm) were collected from each plot to analyze the physical and chemical soil properties. The statistical results showed that latitude, elevation, mean annual maximum temperature, and several soil attributes (i.e., bulk density, field capacity, organic carbon, and pH) were significantly correlated with the SDH. The RT model outperformed the MLR model, explaining 57% of the variation in the SDH with an RMSE of 2.37 m. The maps generated by both models clearly indicated an increasing trend in the SDH from north to south, suggesting that elevation above sea level is a driving factor shaping forest canopy height. The assessments, models, and maps provided by this study can be used by forest planners and land managers, as there is no reliable data on site productivity in the studied region.

Keywords: stand productivity; site factors; multiple linear regression; regression tree; modeling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/19/14580/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/19/14580/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:19:p:14580-:d:1255439

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().