Fennoscandian individual tree basal area increment models for major forest tree species

Abstract

Sustainable forest management needs growth models. Few studies have explored regional models in Fennoscandia despite similar conditions and challenges. We examined the feasibility of regional models for basal area increment of Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pendula Roth. and Betula pubescens Ehrh.). We compiled over 880,000 growth observations and estimated competition indices, climate variables, and site fertility classes by integrating data from recent National Forest Inventories (2004–2023) in Finland, Norway, and Sweden. Using Random Forest models, we identified the main growth drivers across countries (tree size, accumulated temperature sum, latitude, competition, and site fertility), with minor differences in their responses across countries. However, periodic NFI measurements could not capture the effect of additional climate variables. Using species-specific nonlinear mixed models, we demonstrated that predictive regional models can be fitted using those main drivers. Although we achieved only moderate predictive performance (Weighted Absolute Percentage Error of 45–71%, depending on the species and country), there were no residual geographical biases. The results confirm the potential of Fennoscandian growth models to address shared challenges. Future work should better account for site fertility, integrate process-based approaches for climate responses, and carry out independent validation.