Work

Evaluating the performance of mainstream Swedish growth models in uneven-aged forestry systems

Year: 2025

Type: article

Abstract: Continuous Cover Forestry (CCF) practices are increasingly recognized for their potential in climate change adaptation and biodiversity conservation. Selection cutting, a key method within CCF, presents unique challenges for forest growth modeling due to its complex structure and distinct growth dynamics. Current models, largely developed from data obtained from even-aged stands, may exhibit lower accuracy when applied to uneven-aged stands. This study assessed the short-term (i.e., up to 15 years) predictive accuracy of Swedish growth models for tree recruitment, growth, and mortality in uneven-aged stands, utilizing a dataset from field experiments covering a broad latitudinal and environmental range. A linear mixed-effects modeling approach was used to analyse differences between observations and model predictions. Findings revealed potential species-specific biases, with an average underestimation of volume growth by 2 m3 ha−1 yr−1 after ten years of simulation, driven predominantly by underestimations in Norway spruce growth. While mortality predictions were generally accurate, they exhibited slight underestimation after recent cutting and overestimation otherwise. Ingrowth density predictions demonstrated minor biases, with spruce being underestimated and birch overestimated, but displayed high residual variability. Sensitivity analysis revealed correlations of residuals with stand variables, including site index, proportion of spruce, and stand basal area. The study faced limitations due to data scarcity and the short observation periods. Although most observed biases were not statistically significant, the findings underscore potential discrepancies when applying current Swedish models to selection cutting stands. This study emphasizes the need for long-term field trials, further model assessment, and the development of growth models specifically tailored for CCF systems.

Source: Forest Ecology and Management

DOI: 10.1016/j.foreco.2025.122560

Authors: Mateusz Grzeszkiewicz, Alex Appiah Mensah, Martin Goude, Jeannette Eggers, Renats Trubins, Göran Ståhl

Institution: Swedish University of Agricultural Sciences

Language: English

Topic: Forest ecology and management

Subfield: Nature and Landscape Conservation

Field: Environmental Science

Domain: Physical Sciences

SDGs: Life on land, Climate action

Open Access status: hybrid

Estimated APC paid: $3,560