Vulnerability of cork oak woodlands to climate change: a modelling approach

Cofinanciado por:
Project title | Vulnerability of cork oak woodlands to climate change: a modelling approach
Project Code | POCTI/CLI/60413/2004
Main objective |

Region of intervention |

Beneficiary entity |
  • Universidade Técnica de Lisboa - Instituto Superior de Agronomia(líder)
  • Universidade de Évora(parceiro)

Approval date | 24-06-2005
Start date | 01-01-2007
Date of the conclusion | 31-12-2011

Total eligible cost |
European Union financial support |
National/regional public financial support |
Apoio financeiro atribuído à Universidade de Évora | 31663 €

Summary

Cork-oak and other evergreen-oak woodlands in Portugal are very important because of their socio-economic and environmental values. However, they have shown to be vulnerable to climate change and biotic stresses. The sustainability of these ecosystems depends on adaptive management practices for which suitable simulation models are needed. However, the sparse and irregular tree cover of these woodlands renders modeling difficult. In this project, we propose to hybridize the cork oak growth simulator CORKFITS, developed in former research projects, with a process-based model that will allow the quantification of carbon and water fluxes of the tree, shrub and grass components of the ecosystem. The development of this latter will reside on data obtained by one of the proponents as well as on tested models developed for forest simulations. The empirical cork oak growth simulator CORKFITS is a singletree spatial growth simulator composed of growth (cork, stem, tree height and crown), cork production and mortality models (Ribeiro et al., 2003). It includes also a structure generator, STRUGEN which simulates virtual stands as well as regeneration. It will be coupled to the process-based model PROXEL (PROcess-piXEL Model; Falge et al., 2003), broadening the range of outputs and, thus, increasing its applicability, while the large database used for the development of CORKFITS will be also used in the development and calibration of the process-based model. Field data collection will focus largely on (1) stand level leaf area index modeling due to the sparse tree cover and (2) on the shrub and grass layers, for which less data is presently available and via which hydrological balance, fire risk and grazing influences on tree establishment are controlled. The process-based model component will build a link between CORKFITS and time dependent variations in water use and carbon gain, that are controlled by variability in climate and by the soil hydrological water store. The process-based model allows spatial assessment of the influence of vegetation structure (tree, grass and shrubs) on overall water availability during drought, and, thus, production or increased stress. It will produce indices that may be correlated with observed changes in cork oak growth, production, establishment and/or mortality.


Goals, activities and expected/achieved results

The main objective of the project is to use the results of earlier research to develop a hybrid forest growth model for cork oak stands. The objectives are:

- To assemble already existing data (physiological and structural) from former research projects, integrating them in an interactive database for the new model development and completing with new field measurements whenever necessary;

- To develop a process-based model for cork-oak stands based on existing models (e.g. PROXEL) adapted to the geometry of open evergreen oak woodlands (montados), to simulate carbon and water balances;

- To develop a hybrid forest growth model for cork oak stands, coupling process-based models with the observation-based growth model CORKFITS. Such a model will be able to assess the impact of climate change, management and site characteristics on cork oak systems, while providing information useful to managers and policy makers.

- To produce vulnerability indicators for future climate scenarios such as tree mortality, shrub encroachment and shrub biomass (risk of forest fire).

Attribute Type Value
id integer 869