Forest simulation models in Spain: main developments and challenges

Marc Palahí & Carles Gracia

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 2008Vienna, Austria

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-> 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)

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

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

Forest modelling approaches and trends

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. 8:213-230.

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: 23–35.

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 productionBonet, 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 beautyBlasco, 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 forestPablo 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 fluxes in major European forest biomes. Global Change Biology. 11:2211-2233.

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: 169–176.

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.

Pocurr Pdead

Pfire Pdead

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@lugo.usc.es SILVES, delrio@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.htm)

LENGHT OF THE GROWTH PERIOD

(days) 1960-1990

<85

[86,100]

[101,115]

[116,131]

[132,146]

[147,161]

[162,177]

[178,192]

[193,207]

[208,223]

[224,238]

[239,253]

[254,269]

[270,284]

[285,300]

Research highlight

LENGHT OF THE GROWTH PERIOD (days)A2_HadCM3 2020

<85

[86,100]

[101,115]

[116,131]

[132,146]

[147,161]

[162,177]

[178,192]

[193,207]

[208,223]

[224,238]

[239,253]

[254,269]

[270,284]

[285,300]

<85

[86,100]

[101,115]

[116,131]

[132,146]

[147,161]

[162,177]

[178,192]

[193,207]

[208,223]

[224,238]

[239,253]

[254,269]

[270,284]

[285,300]

LENGHT OF THE GROWTH PERIOD (days)A2_HadCM3 2050

<85

[86,100]

[101,115]

[116,131]

[132,146]

[147,161]

[162,177]

[178,192]

[193,207]

[208,223]

[224,238]

[239,253]

[254,269]

[270,284]

[285,300]

LENGHT OF THE GROWTH PERIOD (days)A2_HadCM3 2080

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

Modeled changes in the length of the growth periodModeled changes in the length of the growth period

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

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. 2005;10.1126/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