Radial growth models for Pedunculate Oak in the Baltics, Latvia

Agnese Anta Liepiņa, Roberts Matisons, Kārlis Bičkovskis, Guntis Brūmelis and Āris Jansons

Ecological Modelling, 2025, vol. 506, issue C

Abstract: Changes of growth in pedunculate oak Quercus robur L. are anticipated, hence accurate projections of reference growth are needed to evaluate effects of management and climate change on performance of the species. The study aimed to test common tree growth models and calibrate the first radial growth reference model for pedunculate oak in the Baltics. Individual cumulative diameter growth was reconstructed from 178 increment cores sampled from 89 pedunculate oak trees growing in eight plantation stands under constant local density. Six different nonlinear fixed-effects growth models derived using the Generalized Algebraic Difference Approach (GADA) were fitted to the observed growth data. The best model selection was made by evaluating model fit statistics in context with biological realism. Due to mature tree age and continuous diameter data, all six tested radial growth models showed a good fit to observed radial growth. Based on fit statistics and the realism of the projected growth curves, the Strand model showed best performance for predicting radial growth of pedunculate oak in the Eastern Baltic region. This study represents one of the very few known endeavours of the GADA modelling for radial growth of pedunculate oak. The fitted radial growth reference models can further serve as the basis for assessment of the impacts of climate change and management on the species' future growth in the region.

Keywords: GADA; Quercus robur L.; Radial growth; Nonlinear fixed effects models (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380025001462
Full text for ScienceDirect subscribers only

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:eee:ecomod:v:506:y:2025:i:c:s0304380025001462

DOI: 10.1016/j.ecolmodel.2025.111161

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().