1. Forest simulation models in Finland: main developments and challenges WG1 Jari Hynynen, Annikki Mäkelä & Kalle Eerikäinen COST ACTION FP0603: Forest models for research and decision support in sustainable forest management 1st Workshop and Management Committee Meeting. Institute of Silviculture, BOKU. 8-9 of May 2008 Vienna, 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. m 3 annual growth ca 98 mill. m 3 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. 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) Forest modelling approaches and trends

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.