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Simulation and Visualisation of Functional Landscapes: Effects of the Water Resource Competition Between Plants

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Abstract

Vegetation ecosystem simulation and visualisation are challenging topics involving multidisciplinary aspects. In this paper, we present a new generic frame for the simulation of natural phenomena through manageable and interacting models. It focuses on the functional growth of large vegetal ecosystems, showing coherence for scales ranging from the individual plant to communities and with a particular attention to the effects of water resource competition between plants. The proposed approach is based on a model of plant growth in interaction with the environmental conditions. These are deduced from the climatic data (light, temperature, rainfall) and a model of soil hydrological budget. A set of layers is used to store the water resources and to build the interfaces between the environmental data and landscape components: temperature, rain, light, altitude, lakes, plant positions, biomass, cycles, etc. At the plant level, the simulation is performed for each individual by a structural-functional growth model, interacting with the plant’s environment. Temperature is spatialised, changing according to altitude, and thus locally controls plant growth speed. The competition for water is based on a soil hydrological model taking into account rainfalls, water runoff, absorption, diffusion, percolation in soil. So far, the incoming light radiation is not studied in detail and is supposed constant. However, competition for light between plants is directly taken into account in the plant growth model. In our implementation, we propose a simple architecture for such a simulator and a simulation scheme to synchronise the water resource updating (on a temporal basis) and the plant growth cycles (determined by the sum of daily temperatures). The visualisation techniques are based on sets of layers, allowing both morphological and functional landscape views and providing interesting tools for ecosystem management. The implementation of the proposed frame leads to encouraging results that are presented and illustrate simple academic cases.

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References

  1. De Reffye P, Hu B G. Relevant choices in botany and mathematics for building efficient dynamic plant growth models: GreenLab case. In Proc. PMA03, Beijing, 2003, pp.87–107.

  2. Cournède P H. Kang M Z, Mathieu A, Barczi J F, Yan H P, Hu B G, de Reffye P. Structural factorization of plants to compute their functional and architectural growth. Simulation, 2006, 82(7): 427–438.

    Article  Google Scholar 

  3. Hammes J. Modeling of ecosystems as a data source for real-time terrain rendering. In Proc. Digital Earth Moving First International Symposium, DEM 2001, Springer Verlag, LNCS 2181, 2001, pp.98–105.

  4. Fournier A, Fussell D, Carpenter L. Computer rendering of stochastic models. Commun. ACM, 1982, 25(6): 371–384.

    Article  Google Scholar 

  5. Musgrave F K, Kolb C E, Mace R S. The synthesis and rendering of eroded fractal terrains. Computer Graphics, 1989, 23(3): 41–50.

    Article  Google Scholar 

  6. Chiba N, Muraoka K, Fujita K. An erosion model based on velocity fields for the visual simulation of mountain scenery. The Journal of Visualization and Computer Animation, 1998, 9(6): 185–194.

    Article  Google Scholar 

  7. Neidhold B, Wacker M, Deussen O. Interactive physically based fluid and erosion simulation. In Proc. Eurographics Workshop on Natural Phenomena, Dublin, 2005, pp.25–32.

  8. Schneider J, Boldte T, Westermann R. Real-time editing, synthesis, and rendering of infinite landscapes on GPUs. In Proc. Vision, Modeling and Visualization, IOS Press Proceedings, Aachen, Germany, Nov. 22–24, 2006.

  9. Dachsbacher C. Interactive terrain rendering: Towards realism with procedural models and graphics hardware [Dissertation]. University Erlangen-Nürnberg, Computer Sciences Institute, 2006, p.162.

  10. Greene N. Voxel space automata: Modeling with stochastic growth processes in voxel space. In Proc. SIGGRAPH’89, New York, USA, 1989, pp.175–184.

  11. Deussen O, Hanrahan P, Lintermann B, Mãech R, Pharr M, Prusinkiewicz P. Realistic modeling and rendering of plant ecosystems. In Proc. SIGGRAPH’98, New York, NY, USA, 1998, pp.275–286.

  12. Alweis M, Deussen O. Modeling and visualization of symmetric and asymmetric plant competition. In Proc. Eurographics Workshop on Natural Phenomena, Dublin, 2005, pp.83–88.

  13. Liu Y B, Gebremeskel S, De Smedt F, Hoffmann L, Pfister L. Predicting storm runoff from different land use classes using a GIS-based distributed model. Hydrological Processes, 2006, 20(6): 533–548.

    Article  Google Scholar 

  14. Jaeger M, Teng J. Tree and plant volume imaging — An introductive study towards voxelized functional landscapes. In Proc. PMA03, Beijing, 2003, pp.169–181.

  15. Musy A. Cours d’hydrologie générale, EPFL. http://hydram.epfl.ch/e-drologie/.

  16. Beauchamp J. L’eau et le sol. http://www.oleiculteur.com/L’eau%20et%20le%20sol.htm.

  17. Guo Y, Ma Y T, Zhan Z G, Li B G, Dingkuhn M, Luquet D, De Reffye P. Parameter optimization and field validation of the functional-structural model GreenLab for maize. Annals of Botany, 2006, 97: 217–230.

    Article  Google Scholar 

  18. Cournède P H, Mathieu A, Houllier F, Barthélémy D, de Reffye P. Computing competition for light in the GreenLab model of plant growth: A contribution to the study of the effects of density on resource acquisition and architectural development. Submitted, 2007.

  19. Varado N, Braud I, Ross P J. Development and assessment of an efficient vadose zone module solving the 1D Richards’ equation and including root extraction by plants. Journal of Hydrology, 2005, 323(1–4): 258–275.

    Google Scholar 

  20. Vrugt J A, Hopmans J W, Simunek J. Calibration of a two-dimensional root water uptake model. Soil Science Society of America Journal, 2001, 65(4): pp.1027–1037.

    Article  Google Scholar 

  21. Wu L, Le Dimet F X, Hu B G, Cournède P H, De Reffye P. A water supply optimization problem for plant growth based on GreenLab model. ARIMA Journal, Nov. 2005, pp.194–207.

  22. Witelski T P. Motion of wetting fronts moving into partially pre-wet soil. Advances in Water Resources, 2005, 28: 1133–1141.

    Article  Google Scholar 

  23. Kosugi K, Hopmans J W, Dane J H. Water retention and storage — Parametric models. Soil Science Society of America, 2002, Volume 5, pp.739–758.

    Google Scholar 

  24. Beven K J, Kirkby M J. A physically based variable contributing area model of basin hydrology. Hydrological Sciences Bulletin, 1979, 24(1): 43–69.

    Article  Google Scholar 

  25. Howard A D. A detachment limited model of drainage basin evolution. Water Resources Research, 1994, 30(7): 2261–2285.

    Article  Google Scholar 

  26. Tarboton D G, A new method for the determination of flow direction and upslope areas in grid digital elevation model. Water Resources Research, 1997, 33(2): 309–319.

    Article  Google Scholar 

  27. Tucker G, Gasparini N, Lancaster S. An integrated hillslope and channel evolution model as an investigation and prediction tool. Annual report, Child model, 1997.

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Correspondence to Vincent Le Chevalier.

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This work is supported by the National Natural Science Foundation of China under Grant No. 60473110 and by LIAMA-GREENLAB Project.

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Le Chevalier, V., Jaeger, M., Mei, X. et al. Simulation and Visualisation of Functional Landscapes: Effects of the Water Resource Competition Between Plants. J. Comput. Sci. Technol. 22, 835–845 (2007). https://doi.org/10.1007/s11390-007-9105-8

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