Annals of Forest Science

, Volume 69, Issue 2, pp 221–233 | Cite as

Capsis: an open software framework and community for forest growth modelling

  • Samuel Dufour-Kowalski
  • Benoît Courbaud
  • Philippe Dreyfus
  • Céline Meredieu
  • François de Coligny
Original Paper



Forest scientists build models to simulate stand growth and forests dynamics. Dedicated computer tools are often developed to implement these models in order to run silvicultural scenarios and explore simulation results.


Our objective was to encourage software reuse and simplify model implementation.


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.


Capsis provides an open and modular software architecture based on various components, allowing to run forest growth simulations and display the results. The benefits of this framework are shown with the Samsara2 model, an individual-based and spatialised tree model. Capsis has been used successfully in many similar projects. In addition, the Capsis methodology defines how developers, modellers and end-users may interact.


The Capsis framework facilitates collaborative and shared software development. Moreover, it is a powerful way to support scientific animation in the frame of forest science.


Forestry Silviculture Software architecture Modelling framework 



The success of Capsis comes from an active collaboration of the different members of the community around the developers and the authors would like to thank them for their diverse and helpful contributions. Special thanks to F.R. Bonnet for giving birth and initial success to Capsis as its first computer engineer and to H. Oswald (INRA) for his efficient work in overcoming initial administrative concerns.


Financial support to the development of the Capsis framework has been provided initially by the French Ministry in charge of forests, by INRA, ONF and AFOCEL, and, from then on, by INRA, namely in the form of permanent staff in charge of this development and of animating the collaborative network.

Supplementary material

13595_2011_140_MOESM1_ESM.odt (31 kb)
Online Resource 1 Capsis model list with short description, contact persons and integration starting date. An up-to-date list can be found at (ODT 31 kb)


  1. Ancelin P, Courbaud B, Fourcaud T (2004) Developing an individual tree-based mechanical model to predict wind damage within forest stands. For Ecol Manag 203:101–121CrossRefGoogle Scholar
  2. Argent RM (2004) An overview of model integration for environmental applications—components, frameworks and semantics. Environ Model Softw 19:219–234CrossRefGoogle Scholar
  3. Argent RM, Rizzoli AE (2004) Development of multi-framework model components. Complexity and integrated resources management. In: Pahl-Wostl C, Schmidt S, Rizzoli AE, Jakeman AJ (eds) Transactions of the 2nd biennial meeting of the international environmental modelling and software society: complexity and integrated resources management (1). International Environmental Modelling and Software Society, ISBN 88-900787-1-5, pp 365–370Google Scholar
  4. Argent RM, Voinov A, Maxwell T, Cuddy SM, Rahman JM, Seaton S, Vertessy RA, Braddock RD (2006) Comparing modelling frameworks—a workshop approach. Environ Model Softw 21:895–910CrossRefGoogle Scholar
  5. Barczi J, Rey H, Caraglio Y, De Reffye P, Barthélémy D, Qiao XD, Fourcaud T (2007) AmapSim: a structural whole-plant simulator based on botanical knowledge and designed to host external functional models. Ann Bot London 101:1125–1138CrossRefGoogle Scholar
  6. Brisson N, Ruget F, Gate P, Lorgeou J, Nicoullaud B, Tayot X, Plenet D, Jeuffroy MH, Bouthier A, Ripoche D, Mary B, Justes E (2002) STICS: a generic model for simulating crops and their water and nitrogen balances. II. Model validation for wheat and maize. Agron Sustain Dev 22:69–92Google Scholar
  7. Chabaud L, Nicolas L (2009) Guide des sylvicultures. Pineraies des plaines du centre et du Nord-Ouest. ONF, ParisGoogle Scholar
  8. Coates KD, Canham CD, Beaudet M, Sachs DL, Messier C (2003) Use of a spatially explicit individual-tree model (SORTIE/BC) to explore the implications of patchiness in structurally complex forests. For Ecol Manag 186:297–310CrossRefGoogle Scholar
  9. Cordonnier T, Courbaud B, Franc A (2006) Permanence of stability properties and protection efficiency in mountain spruce stands. In: Natural disturbance-based silviculture—managing for complexity, IUFRO 1.05 Conference, Rouyn-Noranda, Québec, 14–18 May 2006, ISBN-10: 2-923064-17-8Google Scholar
  10. Courbaud B, Goreaud F, Dreyfus P, Bonnet FR (2001) Evaluating thinning strategies using a tree distance dependent growth model: some examples based on the CAPSIS software “uneven-aged spruce forests” module. For Ecol Manag 145:15–28CrossRefGoogle Scholar
  11. Courbaud B, de Coligny F, Cordonnier T (2003) Simulating radiation distribution in a heterogeneous Norway spruce forest on a slope. Agric For Meteorol 116:1–18CrossRefGoogle Scholar
  12. Cucchi V, Meredieu C, Stokes A, de Coligny F, Suarez J, Gardiner BA (2005) Modelling the windthrow risk for simulated forest stands of Maritime pine (Pinus pinaster Ait.). For Ecol Manag 213:184–196CrossRefGoogle Scholar
  13. de Coligny F, Meredieu C, Labbé T, Vallet P, Dreyfus P (2005) Using Capsis for connection with wood quality. In: Proceedings of the 5th IUFRO workshop on connection between forest resources and wood quality: Modelling Approaches and Simulation Software. Waiheke Island, New Zealand, 20–27 November 2005Google Scholar
  14. Degenne P, Lo Seen D, Parigot D, Forax R, Tran A, Ait Lahcen A, Cure O, Jeansoulin R (2009) Design of a domain specific language for modelling processes in landscapes. Ecol Model 220:3527–3535CrossRefGoogle Scholar
  15. Dreyfus P (2008) Dynamiques du Sapin, du Hêtre et des Pins dans l’arrière-pays méditerranéen: de la modélisation à l’aide à la gestion. Rev For Fr 60:233–249Google Scholar
  16. Dreyfus P, Bonnet FR (1995) CAPSIS, logiciel de simulation de conduites sylvicoles. Rev For Fr 47:111–115CrossRefGoogle Scholar
  17. Dreyfus P, Bonnet FR (1997) Capsis (Computer-Aided Projection of Strategies In Silviculture): an interactive simulation and comparison tool for tree and stand growth, silvicultural treatments and timber assortment. In: Nepveu G (ed) Proceedings of the second IUFRO WP S5.01.04 workshop: connection between silviculture and wood quality through modelling approaches and simulation software, pp 194–202Google Scholar
  18. Dreyfus P, Hamza N, Pignard G (2001) Construction de modèles de croissance pour les peuplements réguliers à partir des données dendrométriques de l’IFN. Rev For Fr 53:434–441Google Scholar
  19. Dreyfus P, Pichot C, de Coligny F, Gourlet-Fleury S, Cornu G, Jésel S, Dessard H, Oddou-Muratorio S, Gerber S, Caron H, Latouche-Hallé C, Lefèvre F, Courbet F, Seynave I (2005) Couplage de modèles de flux de gènes et de modèles de dynamique forestière. Un dialogue pour la diversité génétique—Actes du 5ème colloque national BRG, Lyon, 3–5 Novembre 2004, Les Actes du BRG n°5, ISBN 2-908447-33-9, pp 231–250Google Scholar
  20. Duvall P, Matyas S, Glover A (2007) Continuous integration: improving software quality and reducing risk. Free Software Foundation, Inc. 1999. Addison-Wesley, ReadingGoogle Scholar
  21. Gardiner BA, Quine CP (2000) Management of forests to reduce the risk of abiotic damage—a review with particular reference to the effects of strong winds. For Ecol Manag 135:261–277CrossRefGoogle Scholar
  22. Gauquelin X, Courbeaud B (2006) Guide de sylviculture des forêts de montagne—Alpes du Nord françaises. Cemagref—CRPF Rhône-Alpes—Office National des ForêtsGoogle Scholar
  23. Gauquelin X, Courbaud B, Fay J, Berger F, Mermin E (2008) Conduite de peuplements mélangés en forêt de montagne: exemple d’un transfert chercheurs-gestionnaires. Rev For Fr LX:207–214Google Scholar
  24. Goreaud F, de Coligny F, Courbaud B, Dhôte JF, Dreyfus P, Pérot T (2005) La modélisation: un outil pour la gestion et l’aménagement en forêt. VertigO 6:12Google Scholar
  25. Goreaud F, Alvarez I, Courbaud B, de Coligny F (2006) Long-term influence of the spatial structure of an initial state on the dynamics of a forest growth model: a simulation study using the Capsis platform. Simulation 82:475–495CrossRefGoogle Scholar
  26. Hillyer C, Bolte J, van Evert F, Lamaker A (2003) The ModCom modular simulation system. Eur J Agron 18:333–343CrossRefGoogle Scholar
  27. Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ (2003) An overview of APSIM, a model designed for farming systems simulation. Eur J Agron 18:267–288CrossRefGoogle Scholar
  28. Lacerte V, Larocque GR, Woods M, Parton WJ, Penner M (2006) Calibration of the forest vegetation simulator (FVS) model for the main forest species of Ontario, Canada. Ecol Model 199:336–349CrossRefGoogle Scholar
  29. Le Moguédec G, Dhôte JF (2011) “Fagacées”: a tree-centered growth and yield model for Sessile oak (Quercus petraea L.). Ann For Sci. doi: 10.1007/s13595-011-0157-0
  30. Lemoine B (1991) Growth and yield of maritime pine (Pinus pinaster Ait): the average dominant tree of the stand. Ann Sci For 48:593–611CrossRefGoogle Scholar
  31. Lorek H, Sonnenschein M (1999) Modelling and simulation software to support individual-based ecological modelling. Ecol Model 115:199–216CrossRefGoogle Scholar
  32. Meredieu C, Dreyfus P, Cucchi C, Saint-André L, Perret S, Deleuze C, Dhôte JF, de Coligny F (2009) Utilisation du logiciel Capsis pour la gestion forestière. Forêt-entreprise 186:32–36Google Scholar
  33. Monserud RA, Sterba H (1996) A basal area increment model for individual trees growing in even- and uneven-aged forest stands in Austria. For Ecol Manag 80:57–80CrossRefGoogle Scholar
  34. Moore RV, Tindall CI (2005) An overview of the open modelling interface and environment (the OpenMI). Environ Sci Policy 8:279–286CrossRefGoogle Scholar
  35. Muetzelfeldt R, Massheder J (2003) The Simile visual modelling environment. Eur J Agron 18:345–358CrossRefGoogle Scholar
  36. Muys B, Hynynen J, Palahí M, Lexer MJ, Fabrika M, Pretzsch H, Gillet F, Briceño E, Nabuurs GJ, Kint V (2011) Simulation tools for decision support to adaptive forest management in Europe. Systems 19:96–99Google Scholar
  37. Nguyen DZ, Ricken M, Wong S (2004) Design patterns for marine biology simulation. In: SIGCSE’04: Proceedings of the 35th SIGCSE technical symposium on computer science education. ACM, New York, ISBN: 1-58113-798-2, pp 467–471Google Scholar
  38. Orazio C, Meredieu C, Saint-André L, de Coligny F (2002) Building bridges between modellers and end-users. A case study of Southern Europe. In: Colloque IUFRO, IEFC, ISA on incorporating forest growth models into decision-support tools for sustainable forest management, Lisbon, Portugal, 6–8 June 2002Google Scholar
  39. Ottorini JM (1991) Growth and development of individual Douglas-fir in stands for applications to simulation in silviculture. Ann For Sci 48:651–666CrossRefGoogle Scholar
  40. Papajorgji P (2005) A plug and play approach for developing environmental models. Environ Model Softw 20:1353–1357CrossRefGoogle Scholar
  41. Porté A, Bartelink HH (2002) Modelling mixed forest growth: a review of models for forest management. Ecol Model 150:141–188CrossRefGoogle Scholar
  42. Pradal C, Dufour-Kowalski S, Boudon F, Fournier C, Godin C (2008) OpenAlea: a visual programming and component-based software platform for plant modeling. Funct Plant Biol 35:751–760CrossRefGoogle Scholar
  43. Pretzsch H, Biber P, Dursk J (2002) The single tree based stand simulator SILVA: construction, application and evaluation. For Ecol Manag 162:3–21CrossRefGoogle Scholar
  44. Quesnel G, Duboz R, Ramat E (2009) The virtual laboratory environment—an operational framework for multi-modelling, simulation and analysis of complex dynamical systems. Simul Model Pract Th 17:641–653CrossRefGoogle Scholar
  45. Rahman JM, Seaton SP, Perraud JM, Hotham H, Verrelli DI, Coleman JR (2003) It’s TIME for a new environmental modelling framework. In: MODSIM 2004 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand Inc, Townsville, Australia, pp 1727–1732Google Scholar
  46. Rahman JM, Seaton SP, Cuddy SM (2004) Making frameworks more useable: using model introspection and metadata to develop model processing tools. Environ Model Softw 19:275–284CrossRefGoogle Scholar
  47. Rasinmki J, Mkinen A, Kalliovirta J (2009) SIMO: an adaptable simulation framework for multiscale forest resource data. Comput Electron Agric 66:76–84CrossRefGoogle Scholar
  48. Raymond ES (1999) The Cathedral and the Bazaar. O’Reilly & Associates, Inc., Sebastopol, CAGoogle Scholar
  49. Rigolot E, de Coligny F, Dreyfus P, Dupuy JL, Lecomte I, Pezzatti B, Vigy O, Pimont F (2010) Fuel Manager: a vegetation assessment and manipulation software for wildfire modelling. In: Viegas DX (Ed) ProcEEDINGS of the 6th international conference on forest fire research, University of Coimbra, Portugal. 12 ppGoogle Scholar
  50. Roxburgh SH, Davies ID (2006) COINS: an integrative modelling shell for carbon accounting and general ecological analysis. Environ Model Softw 21:359–374CrossRefGoogle Scholar
  51. Sequeira RA, Olson RL, McKinion JM (1997) Implementing generic, object-oriented models in biology. Ecol Model 94:17–31CrossRefGoogle Scholar
  52. Tang S, Meng CH, Meng FR, Wang YH (1994) A growth and self-thinning model for pure even-age stands: theory and applications. For Ecol Manag 70:67–73CrossRefGoogle Scholar
  53. Vieilledent G (2009) Structurer l'incertitude et la variabilité dans les modèles de dynamique forestière. Application à la coexistence du Sapin et de l'Epicéa en forêt de montagne. Thèse, AgroParisTech-ENGREF, NancyGoogle Scholar
  54. Vieilledent G, Courbaud B, Kunstler G, Dhôte JF (2010a) Mortality of Silver fir and Norway spruce in the western Alps—a semi-parametric approach combining size-dependent and growth-dependent mortality. Ann For Sci 67:305CrossRefGoogle Scholar
  55. Vieilledent G, Courbaud B, Kunstler G, Dhôte JF, Clark JS (2010b) Individual variability in tree allometries determines light resource allocation in forest ecosystems—a hierarchical Bayes approach. Oecologia 163:759–773PubMedCrossRefGoogle Scholar
  56. Vincent G, de Foresta H (1998) A three dimensional dynamic model of Damar agroforest in Sumatra (Indonesia). In: Enriquez GL, Wasrin UR and Murdiyarso D (eds) Tropical forest dynamics. Biotrop Special Publication No. 60. pp 139–157Google Scholar
  57. Wernsdörfer H, Caron H, Gerber S, Cornu G, Rossi V, Mortier F, Gourlet-Fleury S (2009) Relationships between demography and gene flow and their importance for the conservation of tree populations in tropical forests under selective felling regimes. Conserv Genet. doi: 10.1007/s10592-009-9983-0

Copyright information

© INRA and Springer-Verlag, France 2011

Authors and Affiliations

  • Samuel Dufour-Kowalski
    • 1
  • Benoît Courbaud
    • 2
  • Philippe Dreyfus
    • 3
  • Céline Meredieu
    • 4
  • François de Coligny
    • 1
  1. 1.INRA, UMR931 AMAP, Botany and Computational Plant ArchitectureMontpellier Cedex 5France
  2. 2.CEMAGREF, Mountain Ecosystems Research UnitSaint Martin d’HèresFrance
  3. 3.INRA, UR629 URFM, Écologie des Forêts MéditerranéennesAvignon Cedex 9France
  4. 4.INRA, UMR1202 BIOGECOCestas CedexFrance

Personalised recommendations