Title: Forest simulation models in Spain: main developments and challenges
1COST 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
2Main 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)
3Forest 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
4Forest 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.
5Modelling 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. -
6Models 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.
7Simulators 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)
8Research highlight
LENGHT OF THE GROWTH PERIOD (days) 1960-1990
9(No Transcript)
10LENGHT OF THE GROWTH PERIOD (days) A2_HadCM3 2020
11LENGHT OF THE GROWTH PERIOD (days) A2_HadCM3 2050
12LENGHT OF THE GROWTH PERIOD (days) A2_HadCM3 2080
13Modeled 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
14Future 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
15Innovative 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