Implementing individual tree-growth models for optimising the
management of Pinus silvestris, Pinus nigra and Pinus halepensis
any-age forests in Catalonia
Project leader
Palahí, Marc (marc.palahi(at)ctfc.es)
Schedule
13.12.2004 – 13.12.2007
Co-ordinator
Forest Technology Centre of Catalonia (CTFC)
Objectives
Forests dominated by Pinus sylvestris, Pinus nigra and Pinus
halepensis occupy 70% of the forest area of Catalonia. Efficient and
sustainable forest management and planning of these forests is very
important to Catalonian forestry because of their economic,
ecological and social role. The task of forest management planning
is to show the optimal way to use forest resources in a way that the
welfare of the forest owner (and/or the society) is maximised within
the limits set by the legislation. The technological and
methodological development of forest science allows for efficiently
solving complex problems of forest management by using appropriate
simulation tools and quantitative methods relying on numerical
optimization. A key issue in the decision-making process of forest
management planning is to predict forest stand development under
different silviculture regimes. Growth and yield models are needed
to predict the economic returns of a particular management schedule,
but they can also provide key information about the dynamic change
of less tangible attributes of forest, such as aesthetic value, or
suitability of the forest for different animal species as well as to
provide relevant information for fire risk control. Furthermore,
finding the optimal stand management schedule can be a very complex
problem because of the many interrelated variables that need to be
found as well as the many potential objectives which can be
important. In this context, simulation-optimization systems which
combine the use of growth models and numerical optimization
techniques offer the best possible tool to explore, to study and
find the optimal silviculture regime for any specific situation and
objectives. However, the majority of forests cannot be managed
relying only on the stand-level approach because this often produces
large fluctuations in annual harvests and revenues. Thus, in many
cases the optimal stand treatment will depend and should be
coordinated with the rest of the forest property, calling for
forest-level management planning. In this context, simulation tools
are critical to produce reliable information about alternative
treatment schedules for the stands. This information can be later
collected into a forest level optimization model, which is solved by
combinatorial heuristic techniques. Results from a stand level
simulation-optimisation system can be also used to generate
silviculture instructions that can guide the forest level planning.
The main objectives of the project will be on:
1. Developing, evaluating and validating simulation tools for Pinus
sylvestris, Pinus nigra and Pinus halepensis stands in Catalonia.
The simulation tools will be based on:
a) Already existing individual-tree level models developed by the
applicant team.
b) Static diameter distribution models to be develop within the
project and based on the Spanish National Forest Inventory.
2. Generating silvicultural guidelines using the simulation tools
developed as well as stand-level numerical optimization techniques.
The use of simulation-optimisation systems will be demonstrated
within the framework of traditional and emerging stand-level forest
management problems (different situations and objectives;
considering biodiversity, the risk of fires, etc.) for the species
studied.
3. Developing new forest management models that may integrate
traditional wood products as well as explicit stand and landscape
level structural objectives related to ecological or recreational
goals. This will be based on a quantitative approach that can take
advantage of the simulation models developed earlier and new
combinatorial optimization techniques (genetic algorithms, tabu
search, simulated annealing, etc.). Several multi-objective forest
management planning problems will be solve by using the whole chain
of tools and techniques developed during the project.