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Forest simulation models in Spain: main developments and challenges

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Title: Forest simulation models in Spain: main developments and challenges


1

COST ACTION FP0603 Forest models for research
and decision support in sustainable forest
management
  • Forest simulation models in Spain main
    developments and challenges
  • Marc Palahí Carles Gracia

1st Workshop and Management Committee
Meeting.Institute of Silviculture, BOKU.8-9 of
May 2008Vienna, Austria
2
Main features of Spanish forests
  • Forest cover (total/share)
  • 15 mil. ha/ 30 of land
  • 12 mil. of other forest lands
  • Growing stock, annual growth and cuts
  • 675 mil. m3, 35 mil m3 y-1, 50 of the annual
    growth is cut
  • Main species
  • P. halepensis, P. pinaster, P. sylvestris, P.
    nigra, P. pinea, Q. ilex, Q. suber.
  • Main non-wood products and services
  • cork, mushrooms, pine kernels
  • soil protection, hunting, biodiversity,
    recreation
  • Main risks
  • Forest fires
  • Effects of climate change (droughts, etc)
  • new problems balance GPP/respiration (reserve
    carbohydrates-gt dieback)
  • 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 unevenaged
  • Specialised areas on plantations (North-west of
    Spain)

3
Forest modelling approaches and trends
  • Empirical models
  • The trend has been towards individual tree-level
    modelling due to the type of forests and
    silvicultural systems.
  • Tree level models exist for the main coniferous
    trees and Q. suber.
  • Diameter distribution models for the main species
    in given areas to implement individual-tree
    models with stand-level data.
  • Recent research is concentrating in
  • Modelling regeneration
  • Modelling site quality in uneven-aged and mixed
    forests
  • Modelling non-timber products and services
  • Modelling risk of forest fires
  • Developing forest management information systems
    based on models

4
Forest modelling approaches and trends
  • Mechanistic models
  • GOTILWA (Growth of Trees Is Limited by Water)
    (www.creaf.uab.es/gotilwa/), is a process based
    model to simulate growth processes and how is
    influenced by climate, tree stand structure,
    management techniques, soil properties and
    climate change.
  • The Gotilwa model simulates carbon and water
    fluxes

GRACIA C.A., TELLO E., SABATÉ S. i BELLOT (1999).
GOTILWA An integrated model of water dynamics
and forest growth. A RODÀ F., RETANA J., GRACIA
C. i BELLOT J. (eds.), Ecology ofMediterranean
Evergreen Oak Forests. Ecological Estudies, 137
163-179. K KRAMER, I LEINONEN, HH BARTELINK, P
BERBIGIER, M BORGHETTI, CH BERNHOFER, E
CIENCIALA, AJ DOLMAN, O FROER, C GRACIA, A
GRANIER, T GRÜNWALD, P HARI, W JANS, S KELLOMÄKI,
D LOUSTAU, F MAGNANI, G MATTEUCCI, GMJ MOHREN, E
MOORS, A NISSINEN, H PELTOLA, S SABATÉ, A
SANCHEZ, M. SONTAG, R VALENTINI, T VESALA  2002.
Evaluation of 6 process-based forest growth
models based on eddy-covariance measurements of
CO2 and H2O fluxes at 6 forest sites in Europe.
Global Change Biology. 8213-230.
5
Modelling non-timber products and services
  • Pine cones and seed production
  • Calama, R., Montero, G. 2007. Cone and seed
    production from stone pine (Pinus pinea L.)
    stands in Central Range (Spain). Eur J. Forest
    Res. 126 2335.
  • Cork growth and yield,
  • Sánchez-González, M., Calama, R., Cañellas, I.,
    Montero, G. 2007. Variables influencing cork
    thickness in spanish cork oak forests A
    modelling approach. Ann. For. Sci. 64 (2007)
    301-312.
  • Mushroom production
  • Bonet, J.A., Pukkala, T., Fischer, C.R., Palahi,
    M., Aragón, J.M., Colinas, C. 2008. Empirical
    models for predicting the production of wild
    mushrroms in Scots pine (Pinus sylvestris L.)
    forests in the Central Pyrenees. Ann. For. Sci.
    65.
  • Scenic beauty
  • Blasco, E., Rodrigéz-Veiga, P., González, J.R.,
    Pukkala, T., Kolhemainene, O., Palahí, M. 2008.
    Predicting Scenic Beauty of forest stands in
    Catalonia (North-east Spain). Manuscript.
  • Water yield and trade-offs of water and forest
  • Pablo Morales, Martint.Sykes, I.Colin Prentice,
    Pete Smith, Benjamin Smith, Harald Bugmann,
    Barbel Zierl, Pierre Friedlingstein, Nicolas
    Viovy, Santi Sabate, Anabel Sanchez, Eduard Pla,
    Carlos Gracia, Stephen Sitch, Almut Arneth and
    Jerome Ogee. 2005. Comparing and evaluating
    process-based ecosystem model predictions of
    carbon and water ?uxes in major European forest
    biomes. Global Change Biology. 112211-2233.

6
Models for predicting risk of hazards
  • Fire probability
  • Gonzalez, J. R., Palahí, M., Trasobares,
  • A., Pukkala, T. 2006 A fire probability
  • model for forest stands in Catalonia.
  • Annals of Forest Science 63 169176.
  • Fire damage
  • González, J. R. Trasobares, A. Palahí, M.
  • Pukkala, T. 2007. Predicting tree survival
  • in burned forests in Catalonia
  • (North-East Spain) for strategic forest
  • planning.
  • Annals of Forest Science, 64 733-742.

7
Simulators and information systems
  • Model archives
  • SIMANFOR (www.palencia.uva.es/simanfor)
  • Inventory
  • SiBosc (Forest information system for Catalonia)
  • (http//www.creaf.uab.es/sibosc/index.htm)
  • Stand level simulators
  • GESMO, algonjg_at_lugo.usc.es
  • SILVES, delrio_at_inia.es
  • RODAL, (www.forecotech.com)
  • Forest and Regional level simulation-planning
    systems
  • MONTE, multi-objetive forest planning
    (www.forecotech.com)
  • ESCEN, regional scenarios simulator
    (www.forecotech.com)
  • Process based simulators
  • GOTILWA (http//www.creaf.uab.es/gotilwa/index.h
    tm)

8
Research highlight
LENGHT OF THE GROWTH PERIOD (days) 1960-1990
9
(No Transcript)
10
LENGHT OF THE GROWTH PERIOD (days) A2_HadCM3 2020
11
LENGHT OF THE GROWTH PERIOD (days) A2_HadCM3 2050
12
LENGHT OF THE GROWTH PERIOD (days) A2_HadCM3 2080
13
Modeled changes in the length of the growth period
1960-1990 2020 2050 2080
Noruega 124 129 130 155
Finlandia 128 133 142 160
Suecia 135 138 143 165
Italia 190 198 207 228
España 201 213 222 245
Grecia 205 219 223 250
Portugal 218 238 251 279
Europa 169 176 184 205
14
Future challenges
  • Defining needs for new variables in forest
    inventories/modelling plots.
  • To improve the understanding of the trade-offs
    between forest growth and water use
  • How to simulate mixed forests in process-based
    models complexity of species interaction.
  • Hybridizing models to optimize the trade off
    between the management applications and
    process-based.
  • Modelling open forest areas, maquis, rangelands,
    etc.
  • Non-timber products and services
  • Modelling risk and forest regeneration and
    succession (after hazards)
  • Closing gaps between modelers-end users

15
Innovative references
  • Bonet, J.A., Pukkala, T., Fischer, C.R., Palahi,
    M., Aragón, J.M., Colinas, C. 2008. Empirical
    models for predicting the production of wild
    mushrroms in Scots pine (Pinus sylvestris L.)
    forests in the Central Pyrenees. Ann. For. Sci.
    65.
  • Schröter et al. 2005. Ecosystem Service Supply
    and Vulnerability to Global Change in Europe.
    Science 310 (5752), 1333-1337. (Published online
    first 27 Oct. 200510.1126/science.1115233
    Science Express).
  • González, J. R. Trasobares, A. Palahí, M.
    Pukkala, T. 2007. Predicting tree survival in
    burned forests in Catalonia (North-East Spain)
    for strategic forest planning.
  • Keenan, T., Garcia, R., Sabate, S., Gracia, C.
    2007. PROCESS BASED FOREST MODELLING A THOROUGH
    VALIDATION AND FUTURE PROSPECTS FOR MEDITERRANEAN
    FORESTS IN A CHANGING WORLD. Cuadernos de la
    SECF 81-93.
  • Calama, R., Mutke, S., Gordo, J, Montero, G.
    2008. An empirical ecological-type model for
    predicting stone pine (Pinus pinea L.) cone
    production in the Northern Plateau (Spain).
    Forest Ecology and Management 255 (3/4) 660-673
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