Analiza izbranih drevesnih modelov razvoja gozdov, primernih za modeliranje na velikoprostorski ravni, in možnosti njihove uporabe v Sloveniji
Analysis of selected single-tree growth models suitable for large-scale modelling and their potential use in Slovenia

slovenian

2023

forecasting   forest development   forest development simulator   forest policy   large-scale forest inventory   modelling   permanent sample plots

Gozdarski inštitut Slovenije
(Obvezni izvod spletne publikacije)

This article discusses single-tree growth models, which have become an important tool for decision-making, management and strategic decisions in the field of forest management. In Slovenia, we have only recently begun systematic development in the field of forest modelling, which includes the development of a matrix population model, testing selected models from abroad and the development of individual model components. The goal of our work is to introduce the field of empirical single-tree models for modelling forest development on a larger scale. We provide a detailed overview of established methods for modelling individual components of tree models, such as radial and height growth, crown recession, mortality, and recruitment and regeneration. We evaluated the suitability of the selected models from the perspective of their applicability in Slovenia. We conclude that the SILVA, WEHAM, MASSIMO and CALDIS models have the greatest potential for use in Slovenia, as they are all suitable for the different forest types and mixed forests with different structure that prevail in Slovenia. In addition to testing the existing models, we propose the development of new models adapted to the heterogeneous and mixed stands in Slovenia. We also propose expanding the set of indicators in forest inventories and measuring additional tree characteristics, such as canopy characteristics, which would expand forest modelling opportunities in Slovenia. In the conclusions, we also discuss the potential use of machine learning in forest development modelling, as this type of model could represent the next generation of forest models.

10.11.2023