Forest simulation models in Finland : main developments and challenges WG1 Jari Hynynen, Annikki Mäkelä & Kalle Ee

1. COST ACTION FP0603: Forest models for research and decision support in sustainable forest management Forest simulation models in Finland: main developments and challenges WG1 Jari Hynynen, Annikki Mäkelä & Kalle Eerikäinen 1st Workshop and Management Committee Meeting.Institute of Silviculture, BOKU.8-9 of May 2008Vienna, Austria

2. Main features of Finnish forests • Forest cover (total/share): 21.9 mill. ha (72 % of land area) • Growing stock, annual growth and cuts: • ca 2000 mill. m3 • annual growth ca 98 mill. m3 • annual cuts 56 miil • Main species: Scots pine, Norway spruce, birch sp., European aspen, alder sp. • Main non-wood products and services: • moose hunting • nature tourism • reindeer meet production • berries, mushrooms • Main risks • 4 % of the forest area severely damaged, 23 % moderately damaged • damage agents: abiotic (wind, snow), fungi, moose, insects • Management and silvicultural characteristics: • mainly even-aged forestry • typical management program • artificial or natural regeneration (incl. site preparation) • precommercial thinning • commercial thinnings • rotation 50-120 years (depending on site and tree species)

3. Forest modelling approaches and trends Empirical models Main types of models developed • extensive resrearch on modelling covers all types of growth and yield models • most widely applied models are distance-independent individual-tree models Trends in modelling • model evaluation and reliability of simulation systems • models for multipurpose forest management • biomass and carbon sequestration • deadwood dynamics and other valuable stand characteristics for forest biodiversity • wood properties • modelling of stand structure and development based on multi-source inventory data • comprehensive analysis of the whole value chain of forestry (from seed to the end-product)

4. Forest modelling approaches and trends Mechanistic models Main types of models developed • stand growth models based on carbon balance including tree population dynamics • a lot of supporting work on photosynthesis and other processes, tree physiology • modular approaches with summary models Trends in modelling • prediction of regional scale productivity from weather and inventory data • process models predicting wood quality and yield • models for multipurpose forest management • biomass and carbon sequestration • deadwood dynamics and other valuable stand characteristics for forest biodiversity • wood properties • comprehensive analysis of the whole value chain of forestry (from seed to the end-product)

5. Modelling non-timber products and services Models for non-timber products • berry and mushroom yields • yield of lichen for reindeer forage Indicators of biodiversity • occurence of epiphytic lichens, fungi, and some beetle species

6. Models for predicting risk of hazards • risk assessment models of abiotic damages • wind (probability of disturbance and mechanistic models) • snow • risk assessment models of biotic damages • root rot and other pathogens • sawfly • moose

7. Simulators and information systems List existing forest simulators or decision support systems • Stand-level simulators • MOTTI - a stand-level analysis and decision support tool (Metla): www.metla.fi/metinfo/motti/index-en.htm • SMA - a stand-level simulation-optimization tool (University of Helsinki) • SIMO - open source forest management planning software(University of Helsinki) • Forest level decision support systems • MELA - a forestry model and an operational decision support system (Metla): www.metla.fi/metinfo/mela/index-en.htm • Monsu - forest planning program (T. Pukkala) • Process-based models and simulators • Photosynthesis: SPP (Mäkelä et al. 2006), PreLUED (Mäkelä et al. 2007) • Whole-tree growth over rotation • CROBAS (Mäkelä 1997) • LIGNUM (Perttunen et al. 1996) • Tree structure and wood quality • STEMS: Development of 3D stem structure based on structural regularities and profile theory (Mäkelä 2001) • PipeQual: CROBAS runs stem development (Mäkelä and Mäkinen 2003) • RetroSTEM: empirical height functions run stem development (Mäkelä et al. 2004) • FinnFor - ecological forest process model

8. Research highlight • Growth and yield models are widely applied at all levels of planning • scenarios on the development of forest resources at national and regional levels • scenarios based on NFI-data and produced with MELA-system • model-based approach applied in forest management planning at forest holding-level • private forest owners (coverage of planning ca. 70%) • public forests (Forest and Park Service) • all the major forest companies • models and simulation tools are widely applied in preparation of silvicultural recommendations • thinning guides • determination of rotation length

9. Future challenges • development of planning tools for multipurpose forest management predicting • different "products" from forests (quantity and quality) • alternatives in forest management • risks related to forest management • effects of changing environment (incl. climate change) • reliability of the simulations/scenarios • effects on economics • development of analysis tools for the whole value chain of forestry (from seed to end-product)

10. Innovative references List a maximum of 5 references, the most innovative ones in your country and that provide added value to other countries.