Forest simulation models in Belgium: main developments and challenges

1

COST ACTION FP0603 Forest models for research
and decision support in sustainable forest
management

• Forest simulation models in Belgium main
  developments and challenges
• WG1

1st Workshop and Management Committee
Meeting.Institute of Silviculture, BOKU.8-9 of
May 2008Vienna, Austria
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Main features of Belgian forests

• Forest cover (total/share) 693.000 ha (23)
• Growing stock, annual growth and cuts 4 106 m³
  wood used from own forests,
• In addition 7 106 m³ wood imported
• Main species picea, (scots) pine, beech, birch,
  oak, poplar
• Main non-wood products and services passive
  recreation, nature protection, biodiversity
• Main risks fragmentation, deforestation
• Management and silvicultural characteristics
  small patches, abundant private ownership, high
  productivity management practices

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Forest modelling approaches and trends

• Empirical models
• No own developments
• Recent research is concentrating on mechanistic
  modelling and decision support

4
Forest modelling approaches and trends

• Mechanistic models Which exist
• ANAFORE (ANAlysing FORest Ecosystems), growth, C
  and H2O balance, stand scale
• Main features rather complex, will become user
  friendly, includes effects of changing climate
  (and ozone) and management
• FORUG carbon and water balance model, stand
  scale
• SECRETS growth, C and H2O balance, stand scale
• ASPECTS-WiTCh water, carbon, nitrogen cycles in
  plant and soil, and major cations (Na, K,
  Ca2,Mg2), anions (Cl-, SO4-, HCO3-) and pH in
  soil water, vegetation growth, weathering, etc
  (stand scale)
• CARAIB water and carbon cycles, photosynthesis,
  growth, competition of plant types, plant
  type/species potential ranges (regional,
  continental or global scales)
• C-Fix Main features
• Based on Remote Sensing hence Spatially
  explicit.
• Continental to global scale.
• Includes effects of changing climate, with a
  coupled carbon hydrological
• approach.
• Output (GPP, NPP, NEP) available on the WWWeb.

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Simulators and information systems

• Stand level simulators
• ANAFORE, can be downloaded at http//
  www.simfortree.be
• Forest level decision support systems
• SimForTree decision support system under
  construction, based on ANAFORE
• running Flemish project, http//www.simfortree.be
  
• AFFOREST developed within European project,
  www.sl.kvl/afforest
• C-Fix Operational forest flux production
• http//geofront.vgt.vito.be/geosuccess/relay.do?di
  spatchintroduction

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Research highlight

• Including mechanistic simulation of wood density
  in function of growth/envirmonment/management
  (from pipe theory)
• Multicriteria decision support (allowing multiple
  goals in finding the optimal management
• Including bayesian optimisation and uncertainty
  (underway)
• Application of remote sensing in area and carbon
  flux estimations using the VEGETATION instrument

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Future challenges

• In Belgium forests are very fragmented
• A lot of small patches are in private ownership
  without common management practices.
• Decision support management is needed at the
  forest patch level.
• Multipurpose forestry is required in Belgium
  (because of limited available area). Recreation,
  biodiversity and nature protection are important
  forest functions.

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Innovative references

• Deckmyn G., Verbeeck H., Op de Beeck M.,
  Vansteenkiste D., Steppe K., and R. Ceulemans.
  ANAFORE a stand-scale mechanistic forest model
  that includes wood tissue development and labile
  carbon storage as affected by climate, management
  and tree dominance.
• Garcia Quijano J, Deckmyn G, Moons E, Proost S,
  Ceulemans R, Muys B (2005) An integrated decision
  support framework for the prediction and
  evaluation of efficiency, environmental impact
  and total social cost of domestic and
  international forestry projects for greenhouse
  gas mitigation description and case studies.
  Forest Ecology and Management, 207(1-2) 245 -
  262.
• Garcia-Quijano, J.F., Deckmyn, G., Ceulemans, R.,
  Van Orshoven, J., Muys, B. (2008). Scaling from
  Stand to Landscape of Climate Change Mitigation
  by Afforestation and Forest Management a
  Modeling Approach, Climatic Change, 86397-424.
• Gilliams, S., J. Van Orshoven, B. Muys, H. Kros,
  G.W. Heil and W. Van Deursen, 2005. AFFOREST
  sDSS a metamodel based spatial decision support
  system for afforestation of agricultural land.
  New Forests 30 33-53.
• Goddéris Y., L.M. François, A. Probst, J. Schott,
  D. Moncoulon, D. Labat, D. Viville, Modelling
  weathering processes at the catchment scale with
  the WITCH numerical model. Geochim. Cosmochim.
  Acta 70, 1128-1147, 2006.
• Laurent J.-M., L. François, A. Bar-Hen, L. Bel,
  R. Cheddadi, European Bioclimatic Affinity
  Groups data-model comparisons. Global Planet.
  Change, 61, 28-40, 2008.

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Innovative references

• Van Orshoven, J., Gilliams, S., Muys, B.,
  Stendahl, J., Skov-Petersen, H., Van Deursen, W.,
  2007. Support of decisions on afforestation in
  North-Western Europe with the Afforest-sDSS. In
  Heil, G.W., Muys, B., Hansen, K. (eds.)
  Environmental Effects of Afforestation in
  North-Western Europe From Field Observations to
  Decision Support. Springer Publ., Series Plant
  and Vegetation Vol. 1, 227-247.
• Steppe, K., D.J.W. De Pauw, R. Lemeur and P.A.
  Vanrolleghem. 2006. A mathematical model linking
  tree sap flow dynamics to daily stem diameter
  fluctuations and radial stem growth. Tree
  Physiology 26 257-273.
• Verstraeten W. W. , Veroustraete F., Feyen J,
  2006. On temperature and water limitation of net
  ecosystem productivity Implementation in the
  C-Fix model. Ecological Modelling 199 422.
• Verbeeck, H., R. Samson, F. Verdonck and R.
  Lemeur. 2006. Parameter sensitivity and
  uncertainty of the forest carbon flux model
  FORUG a Monte Carlo analysis. Tree Physiology
  26 807-817.
• Verbeeck H, Samson R, Granier A, Montpied P,
  Lemeur R. Multi-year model analysis of GPP in a
  temperate beech forest in France. 2008.
  Ecological Modelling 21085-103.