A comparison of three modelling approaches for large-scale forest scenario analysis in Finland

• Main Authors: Nuutinen, Tuula, Kellomäki, Seppo
• Format: Article
• Language: English
• Published: Finnish Society of Forest Science 2001-01-01
• Series: Silva Fennica
• Online Access: https://www.silvafennica.fi/article/586

Forests play an important role in the sequestration of carbon dioxide and the storage of carbon. The potential and efficiency of mitigation options in forestry have been studied using large-scale forestry scenario models. In Finland, three models have been applied in attempts to estimate timber production and related carbon budgets. In this study, these models are compared. The oldest, MELA, was designed in the 1970s for the regional and national analysis of timber production. The European Forest Information Scenario Model, EFISCEN, originally a Swedish area matrix model, was developed in the early 1980s. SIMA, a gap-type ecosystem model, was utilised in the 1990s for regional predictions on how the changing climate may affect forest growth and timber yield in Finland. In EFISCEN, only the development of growing stock is endogeneous because the assumptions on growth, and the removal and rules for felling are given exogeneously. In the SIMA model, the rules for felling are exogeneous but the growth is modelled based on individual trees reacting to their environment. In the MELA model, the management of forests is endogeneous, i.e. the growth, felling regimes and the development of growing stock are the results of the analysis. The MELA approach integrated with a process-based ecosystem model seems most applicable in the analyses of effective mitigation measures compatible with sustainable forestry under a changing climate. When using the scenarios for the estimation of carbon budget, the policy makers should check that the analyses cover the whole area of interest, and that the assumptions on growth and management together with the definitions applied correspond with the forestry conditions in question.