Aksel Granhus

Avdelingsleder/forskningssjef

(+47) 977 14 873
aksel.granhus@nibio.no

Sted
Ås - Bygg H8

Besøksadresse
Høgskoleveien 8, 1433 Ås

Sammendrag

Based on data from 58 stands located in three different regions within Norway, this study presents new models for quantifying growth characteristics of young, planted trees of Norway spruce (Picea abies (L.) Karst), a species that forms the backbone of the Norwegian forestry sector. The study focused on well-established, sufficiently stocked plantations to capture their inherent growth patterns. The presented models predict total tree height and the number of years required to reach a diameter at breast height of 5 cm for dominant and average-sized individuals, using common tree- and stand-level metrics. The study’s findings indicate enhanced growth of young spruce stands compared to growth dynamics observed in the 1960–1970s, likely due to improved growing conditions. The models presented here are an improvement over existing similar models and can be used in future forest growth and yield simulations. The study also aimed to provide a means to predict diameter distributions of young spruce plantations. While the results suggested significant differences between observed and predicted distributions, this still represents progress as there are currently no tools to estimate diameter distributions of young spruce plantations in Norway. Further research is recommended to corroborate the findings across a larger number of sites and to consider larger sample plots for potentially more accurate diameter distribution predictions.

Forest illustration

Divisjon for skog og utmark

A Decision Support System for emerging forest management alternatives


This project aims to develop advanced tree growth models using LiDAR-derived, high-density point cloud data to improve the simulation of forest dynamics under close-to-nature silvicultural practices. By modeling tree-level growth in structurally complex and heterogeneous stands, these models will support more accurate, spatially explicit forest simulations and inform sustainable and diversified forest management decisions.

Aktiv Sist oppdatert: 17.10.2025
Slutt: jan 2027
Start: jan 2025