![]() “Choosing a framework (for a specific modelling problem) is an unclear process, driven by many factors not necessarily related to the particular advantages or disadvantages of a software package” (Argent et al. This kind of solution is widely used in environmental modelling but not particularly in forest growth dynamics modelling. A framework provides the following features (Argent 2004): (1) a development environment making model integration, implementation and modification easier (2) a set of domain-specific and reusable libraries and data structures (3) some generic and reusable components for mathematics, visualisation or data manipulation (4) a model execution system based on a simulation paradigm assisting with model execution and analysis processing (5) a user interface to configure the model and run the simulations and (6) a documentation and a test system to ensure software quality. Usually, a framework is designed to address common modelling and engineering issues and intends to reduce the investment needed to develop a model. To avoid these problems, modellers can use modelling frameworks or platforms. ![]() 2003), Prognaus (Monserud and Sterba 1996), Sexi (Vincent and de Foresta 1998), Simcop (Ottorini 1991), FVS (Lacerte et al. We can find in the literature a lot of examples of this implementation strategy: SILVA (Pretzsch et al. It may be difficult to reuse for the implementation of another model and this approach does not address development cost reduction. The resulting code is specific to the paradigm of one model. It also needs investment in ergonomics, documentation and training. However, such an approach is costly, requires extensive development and a good cooperation between modellers and computer scientists. A modeller has complete implementation control and can choose freely a data structure. Generally, it can support various parameter sets and can be adapted to various contexts by changing model inputs. The most common approach in forest growth simulation consists in building a specific computer programme around a given model. In environmental sciences, various approaches have been carried out to implement simulation models (Table 1). To implement a new model, forest growth modellers have to face the following challenges: (1) tackle model development complexity, coding and efficiency, (2) make the models usable by other scientists or forest managers and (3) be able to compare various modelling strategies and examine model outputs and simulation results easily. Their conception and their implementation follow the same tendency. While computational power increases, forest growth models concurrently become more and more complex. To be fully exploited, forest dynamics models must be integrated in simulation tools and decision support systems (Muys et al. Computer simulations allow today to make virtual experiments to explore the effects of a wide range of management scenarios on diverse ecosystem services, diverse types of forests and environment conditions. Foresters have used yield tables and stand density management diagrams for long to estimate wood production. Simulation models of forest growth and dynamics can help foresters in their decision-making process by predicting forest stands natural evolution and the consequences of silvicultural treatments. Moreover, it is a powerful way to support scientific animation in the frame of forest science.įorest managers plan and organise silvicultural treatments to address particular management objectives in terms of yield, economics, diversity, protection or conservation. The Capsis framework facilitates collaborative and shared software development. In addition, the Capsis methodology defines how developers, modellers and end-users may interact. Capsis has been used successfully in many similar projects. The benefits of this framework are shown with the Samsara2 model, an individual-based and spatialised tree model. ResultsĬapsis provides an open and modular software architecture based on various components, allowing to run forest growth simulations and display the results. ![]() The scheme was to develop a framework and methodology allowing to simplify the implementation, integration, simulation and comparison of forest models by providing a set of common and standard tools. Our objective was to encourage software reuse and simplify model implementation. Dedicated computer tools are often developed to implement these models in order to run silvicultural scenarios and explore simulation results. Forest scientists build models to simulate stand growth and forests dynamics. ![]()
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