Forest%20simulation%20models%20in%20Greece:%20main%20developments%20and%20challenges

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

• Forest simulation models in Greece main
  developments and challenges
• WG1-WG2-WG3
• Dr. Ioannis Meliadis Dr. Kostas Spanos
• Forest Research Institute, Thessaloniki, Greece

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

• Forest cover (total/share) 6,513,000 Ha - about
  49.5 of the land (industrial forests 25.4 of
  the land, non-industrial forests 23.9).
• Growing stock, annual growth and cuts
• 138,107,130 m3 (41 m3/Ha) - industrial forests
  (56.10 conifers, 43,90 broadleaves).
• 3,812,538 m3 (2.76) - mean annual growth-
  industrial forests
• 1.14 m3/Ha (2,76) mean annual net increment
  (for all species).
• Main species Fir, Pine, Beech, Oak, Poplar,
  Plane tree
• Main non-wood products and services water,
  grazing, game, recreation
• Main risks illegal cutting, fires, biotic
  hazards, drought
• Management and silvicultural characteristics
• Plenty of unmanaged forests- Low profitability of
  timber
• High value of some non-timber products and
  services
• Complex forests mixed and irregular
• Specialised areas on plantations (mainly poplars
  and pines)

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Main features of high forests in Greece

• Forest cover (total/share)
• 25.124.180 ha - 19,63
• Growing stock, annual growth and cuts
• 153,5 mil m3, 4 m3/year (2,3 for coniferous and
  1,5 m3/ha for broadleaves), 2,5 mil m3 (or 1,2
  /ha/year)
• Main species
• Quercus spp (22,6), Pinus nigra (8,72), Abies
  cephalonica (8,34), Fagus silvatica (5,17),
  Pinus nigra (4,33).
• Main non-wood products and services
• Biodiversity, recreation, soil protection, water
  source protection, hunting.
• Main risks
• Forest fires, overgrazing, drought, air
  pollution, illegal cuttings and land use changes.
  
• Management and silvicultural characteristics
• - Bad forest quality and health
• - non strategic plants for the next years

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Forest modelling approaches and trends

• Empirical models
• Main types of models developed
• Tree level models exist for the main forest trees
  species.
• Diameter distribution models for the main species
  in given areas to implement individual-tree
  models with stand-level data.
• Trends in modelling
• The trend has been towards individual tree-level
  modelling due to the type of forests and
  silvicultural systems.
• Recent research is concentrating in
• Modelling regeneration
• Modelling site quality in uneven-aged and mixed
  forests
• Modelling non-timber products and services
• Modelling risk
• Developing forest management information systems
  based on models
• Trends in modelling
• The existing trend in modelling can be found in
  some research programs, but is to ebvaluate
  existing models.
• Recent research is concentrating in
• Forest fire models, biodiversity, soil erosion,
  GIS-based forest information system.

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Forest modelling approaches and trends

• Mechanistic models

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Examples of GROWTH MODELS in Forestry in Greece
(Developed by the FRI in Athens Lab. of Silviculture and Forest Genetics)
Model for Pinus halepensis (Alepo pine) a1 (HE)(EXP(16.52095/ dHE)) h a1(EXP(-16.52095/d)) Va 3.3041044 10-5 d 1.790332 h1.181907 V?  (5.9154438 10 5 d 0.790332 6.451669 10 4 d 0.209668) ( h 1.181907 ) Ve 0.01969779 1.195396 Va ? ??/Va -2.83318 0.3369517d De 3.454176 1.016526 d Da -3.066645 0.9027724 De ??? 60 ?? / 1.1109969 (EXP (-6.315464/A)) D 0.4612958d 0.6681564
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Model for Pinus brutia (calabrian pine)
a1 (HE)(EXP(15.68068/ dHE))
h a1(EXP(-15.68068/d))
Va 2.2000178 10-5 d 1.784734 h1.338171
V?  (3.926447 10 5 d 0.784734 4.616392 10 4 d 0.215266) ( h 1.338171 )
Ve 0.0140711 1.199025 Va
? ??/Va d(EXP(-0.3833344 34.60379 /d))
De 3.665222 1.039437 d
Da -2.188551 0.856878 De
??? 60 ?? / 1.2566101 (EXP (-13.70506/A))
D1 0.4638421d 0.6931317
D2 0.5340905d 0.7210009
D3 0.6468247d 0.7098469
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• Model for Pinus nigra (black pine)
• a1 (HE)(EXP(13.30762/ dHE))
• h a1(EXP(-13.30762/d))
• Va 3.9172327 10-5 d 1.884915 h1.043285
• V?  (7.3836506 10 5 d 0.884915 5.4385449 10
  4 d 0.115085) ( h 1.043285)
• Ve 0.0217237 1.177424 Va
• De 1.663105 1.098303 d
• Da -1.353695 0.8871564 De
• ??? 70 ?? / 1.400907 (EXP (-23.59809/A))
• D d(EXP(-2.129778 6.001434 /d))

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• Model for Abies borissi regis (hybrid fir)
• a1 (HE)(EXP(16.24608/ dHE))
• h a1(EXP(-16.24608/d))
• Va 6.3661346 10-5 d 1.768135 h1.060723
• V?  (1.1256185 10 4 d 0.768135 1.0970499 10
  3 d 0.231865) ( h 1.060723 )
• Ve 0.024065 1.101215 Va
• De 0.7681465 1.211613 d
• Da -0.6885109 0.9633104 De
• ??? 110 ?? / 1.1478617 (EXP (-15.16909/A))
• D 1.64821 0.104426 d

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• Model for Quercus spp. (oak)
• a1 (HE)(EXP(11.72988/dHE))
• h a1(EXP(-11.72988/d))
• Va 2.5182532 10-5 d 1.968549 h1.12419
• V?  (4.9573048 10 5 d 0.968549 3.320723 10 4
  d 0.031451) ( h 1.12419 )
• Ve 0.01631057 1.134771 Va
• ? ??/Va EXP(4.587461 46.14708 /d)
• De 2.061993 1.069939 d
• Da -1.510584 0.9658016 De
• ??? 90 ?? / 1.2380145 (EXP (-19.2158/A))
• D d(EXP(-1.703951 4.191526 /d))

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• Model for Fagus spp. (beech)
• a1 (HE)(EXP(11.81501/ dHE))
• h a1(EXP(-11.81501/d))
• Va 4.0863913 10-5 d 1.985882 h0.9478463
• V?  (8.1150909 10 5 d 0.985882 4.576273 10
  4 d 0.014118) ( h 0.9478463)
• Ve 0.0041674 1.059557 Va
• ? ??/Va EXP(3.6425468 38.90101 /d)
• De 1.786926 1.113821d
• Da -0.43 0.981 De
• ??? 105 ?? / 1.1742275 (EXP (-16.8641/A))
• D 0.71155796 d 0.6468389

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• Where
• a1 a factor selection of a height curve (m)
• HE a mean height for estimation of the above
  factor (m)
• dHE the mean barked diameter at breast height
  corresponding to the above the mean height (cm)
• h a height of a tree (m)
• d the barked diameter of the same tree at
  breast height (cm)
• Va the unbarked stem volume of the same tree
  (m3)
• V?  the stem rise factor of the same tree
  (m3/cm)
• ? ??/Va the percentage of branch wood of the
  same tree with respect to unbarked stem volume ()

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• Ve the barked stem volume of the same tree (m3)
• De the barked stump diameter of the same tree
  (cm)
• Da the unbarked stump diameter of the same tree
  (cm)
• ??? a the site index at an age a, i.e., a 105
  years
• H0 the dominant height of a stand (m)
• A the age of the stand at breast height (years)
• EXP(X) the base e of the neperian logarithms at
  power X
• D crown diameter (m)
• D1 crown diameter for wood production (m)
• D2 crown diameter for wood production with
  tapping (m)
• D1 crown diameter for wood production with
  tapping or tapping and grazing (m)

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Modelling non-timber products and services

• If there are any models for predicting the yield
  of non-timber products or estimating different
  services (scenic beauty, recreation), list them.
  If not skip the slide.
• The Soil Erosion Risk Assessment Maps.
• USLE equation A tn/ha/year R K LS C P
• In this project our institute includes the
  development of methodology and products
  generation (Soil erosion risk maps) using EO data
  and ancillary data into GIS environment.
• See also
• Spanos, K.A., Feest, A., 2007. A review of the
  assessment of biodiversity in forest ecosystems.
  Management of Environmental Quality, 18 (4)
  475-486.

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Models for predicting risk of hazards

• If there are any models for predicting the risk
  (occurrence/damage) of hazards (fires, wind,
  snow, etc), list them. If not skip the slide.
• SPREAD OF Heterobasidion IN STANDS OF Picea and
  Pinus (see MOHIEF project)

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Research highlight

• Describe a country research hihlight/finding in
  the context of modelling which can be relevant
  for other countries
• You can use more than on slide
• See references
• Spanos, K.A., Feest, A., 2007. A review of the
  assessment of biodiversity in forest ecosystems.
  Management of Environmental Quality, 18 (4)
  475-486.
• Woodward, S., J.E. Pratt, T. Pukkala, K.A.
  Spanos, G. Nicolotti, C. Tomiczek, J. Stenlid, B.
  Marçais P. Lakomy, 2002. MOHIEF MODELLING OF
  HETEROBASIDION IN EUROPEAN FORESTS, AN EU-FUNDED
  RESEARCH PROGRAMME.

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Future challenges

• To collaborate with other experts on forest
  models.
• To develop forest models for biodiversity
  indicators to use in forest biodiversity
  assessment and monitoring.
• To develop forest models to predict the effect of
  climate change on biodiversity quality.
• To improve the sustainable forest management
  practices.
• To incorporate the experience of other
  institutions to into our research plans.
• To facilitate our scope for our models for the
  Greek reality.

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Innovative references

1. Apatsidis, L.D., Ziagas, E.Ch., Perris, I.G.,
   Sotiropoulos, D.S., Tziovaras, E.Z., 1999. Models
   for Haleppo pine, Calabrian pine, Black pine,
   Fir, Oak and Beech. Forest research (New Series)
   Vol. 12, 104 p.. National Agricultural Research
   Foundation (N.AG.RE.F.), Athens (in Greek with
   English summary).
2. Kaloudis, S., A. Roussos and P. Kerkides, 1999
   "Investigation of mountainous vegetation
   characteristics using GIS technology",
   International Journal of Balkan Ecology, 2 (3),
   58-73
3. Spanos, K.A., Feest, A., 2007. A review of the
   assessment of biodiversity in forest ecosystems.
   Management of Environmental Quality, 18 (4)
   475-486.
4. Toth, B.B., Feest, A., 2007. A simple method to
   assess macrofungal sporocarp biomass for
   investigating ecological change. Can. J. Botany
   85 652-658.
5. Woodward, S., J.E. Pratt, T. Pukkala, K.A.
   Spanos, G. Nicolotti, C. Tomiczek, J. Stenlid, B.
   Marçais P. Lakomy, 2002. MOHIEF MODELLING OF
   HETEROBASIDION IN EUROPEAN FORESTS, AN EU-FUNDED
   RESEARCH PROGRAMME.