The PAYSAGRI model: from agricultural plot to landscape

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(1)Référence complète de la publication : Type : Poster Colloque : CABM-HEMA-SMAGET, Joint conference on Multi-Agent Modelling for Environnemental Management, 21-25 mars 2005 à Bourg St Maurice. DÉPIGNY S., POIX C. & CHEVILLOT B., 2005. The PAYSAGRI model : from agricultural plot to landscape. CABM-HEMA-SMAGET, Joint conference on Multi-Agent Modelling for Environnemental Management, 21-25 mars à Bourg St Maurice. Poster..

(2) The Paysagri model :. UMR METAFORT. from agricultural plot to landscape. CEMAGREF, ENGREF, ENITAC, INRA. Dépigny S., Poix C., Chevillot B. depigny@enitac.fr, poix@enitac.fr, chevillo@enitac.fr. Issue. We think that landscape changes can't be studied without considering economic activities. For countryside with pastureland, we choose to model the relationship between agricultural activities and the evolution of the major part of land.. Nowadays, countryside-planning projects are often centered on landscape concerns. But the many ways to view landscape and the lack of knowledge are sources of misunderstanding and deadlocks.. The Paysagri model Spatial modelling. Farming modelling. Landscape is like a puzzle. The variation of each landscape piece is the result of specific processes. In the Paysagri model, we choose to focus on pieces, which evolve according to farming practices. Other pieces are supposed to be fixed.. Each farmer plans the farming year, and allocates uses to each plot by balancing two standards :. The elementary piece is the agricultural plot. Actually, each farmer's decision (grazing, cutting, maintenance, clearing…) is taken at this scale. Each plot is defined by its characteristics (area, owner, slope, suitability, capabilities…) stored in a Geographical Information System. The plot vegetation cover is the variable observed.. !. Forage system balance : the management of grazing and cutting must meet animal feed requirements. !. Perception of his landscape impact : each farmer performs "maintenance practices" or "clearing practices" according to his own expectations of DE CI scenery S IO. N ing year Farm. PRACTICE. Forecasting Clearing Herb sowning. Grazing and cutting allocation. Plot 90. Plot maintenance. Forage system balance. AS S. Landscape perception. S ES. M. EN. T. The Paysagri software Simulation duration : 5 to 20 years Time step for farmer’s decisions : 3 months Time step for output variables : 1 year. Created from an object oriented modelling, the Paysagri simulator has been implemented by using the Python programming language.. 7. 6. 2. 8. 10 9. 11. 15. 5. 19. 33 34. 41 36. 42. 31. 29. 37 43. 44. 39 40. 51. 50. 55. 54. 53. 41. 36. 58. 62. 50. 73. 81. 31. 40. 35. 49. 46. 81. 93. 60. 73 79. 90. 80. 74. Year 1 Unused for less than 8 years Unused for more than 8 years Permanent pasture Sown pasture. 36. 42. 10. 62. 50. 87 92. 26. 40. 31. 37. 48 47 51 55 54. 35. 49. 46. 60 69. 66 75 81 85. 73 79. 74. 62. 36. 50. 42. 92. 20 26. 37 43. 48 47 51 55 54. 35. 40. 49. 45 53 60. 69 73 81. 79. 90. 93. 76. 77. 80. 84 88. 89. 68. 70. 66 75. 82 85. 56. 64. 61. 72. 38 46. 57. 63. 17. 16. 18. 24. 31. 29 44. 39. Farm stocking rate. 74 78. 71. 83 86 91. 87 92 93. Cleared areas per year Farmer A. 10. Farmer B. 9 8. 5. 14. 32. 34. 58. 87. 11 19. 21. 59 65 67. 83 91. 94. Year 3. 10 15. 12 28. Years 1.6. 4. 2. 8 9. 25. 52. 56. 71. 78. 86. 90. 93. 41. 68. 70 76 80. 77 84 88. 89. 33. 30. 38. 27. 45 53 64. 61. 72 82. 7. 22. 23. 43. 44. 57. 63. 17. 16. 18. 24 29. 39. 58. 83. 20. 32. 34. 6 13. 5. 14 19. 21. 59 65 67. 71. 91. 11. 15. 12 28. 78. 86. 4. 2. 8 9. 25. 52. 56. 68. 70 76. 77 84 88. 89. 94. 94. 41. 64 69 66. 75. 85. 27 33. 30. 38. 45 53. 57 61. 58 72 82. 90. 37. 48 47 51 55 54. 87 92. 89. 7. 22. 23. 43. 44. 59. 67. 74. 84. 26. 17. 16. 18. 24 29. 39. 78 80. 79. 86 85. 20. 32. 34. 6 13. 5. 14 19. 21. 63. 70. 76 77. 75. 65. 68. 69. 66. 72. 82. 42. 11. 15. 12 28. 52. 56 60 64. 63. 67. 10 9. 25. 45. 49. 57 59 65. 33. 30. 38 46. 47. 48. 52 62. 27. 4. 2. 8. 22. 23. 18. 24 26. 28 30. 17. 16. 20. 25. 7. 13. 14. 12 21. 27. Results. 3. Animal unit / ha. 6. 13 22 23. 3. 3. 3. Example : for a land with 100 plots and 2 farmers, a 10 year simulation takes about 2 minutes with a Pentium III 500Mhz computer.. Farmer B. 7. 1.4 6 5. Farmer A. 1.2. 4 3 2. 94. Year 5. Year 10. Years. 1. 1. Maps of vegetation cover plots. 2. 3. 4. 5. 6. 7. 8. 9. 10. Areas (hectares). 1. 0. 10. 20. 30. 40. Stored data : stocking rate, cleared areas, plots uses.... Mosaic pattern. Prospects The reasoning process used to build the Paysagri model gave us elements to make people understand the relationship between the evolutions of agricultural systems and landscape changes. After validation, we expect the Paysagri model to be used to measure the impacts of agricultural policies on countryside landscape. SMAGET Conference - Bourg-St-Maurice (74) - 21-26 March 2005.

(3) The Paysagri model : from agricultural plot to landscape S. Dépigny, C. Poix, B. Chevillot ENITA Clermont-Ferrand - UR REPER. Nowadays, social reorganization of rural territories is topical issue. More and more people, who don’t belong to agricultural corporations, live on these territories. This phenomenon creates some disagreements. On the one hand, new residents think that landscape is only their living environment. According to them, landscape must be suitable for hobbies. New residents wish this landscape not to evolve. On the other hand, farmers don’t understand these new expectations, which sometimes contradictory their activity. This situation results from a lack of knowledge about the processes of landscape evolution. For agronomist point of view, these processes are deeply linked to agricultural system changes. One cannot see landscape just as a picture of a territory, but more as the result of economic activities. The main objective of our model is to clarify and to explain relationships between public policies, agricultural system changes and landscape changes. Two stages are necessary for this modelling. Firstly, we must understand how public policies are applied and how these policies change strategies of agricultural systems. Secondly, we try to assess landscape evolutions, which are due to the reorganization of agricultural systems. Our modelling is based on medium altitude areas where the main part of land is managed by agricultural systems. The Paysagri model is based on three concepts : The landscape is the measured variable. Considering geoagronomy, landscape can be seen as a puzzle made of many pieces. According to this point of view, each piece is both a component and a consequence of a sociological and economical system. In our model, landscape is a puzzle made of all agricultural plots of the studied territory. The plot is the elementary object in the model. That’s why it is assumed homogeneous ; i.e. the model doesn’t handle phenomena that occur inside the plot. We keep the only information that is essential for the farmer’s decisions. Texture and age characterize a plot. The textures are “natural meadow”, “artificial meadow”, “crop” or “unused”. The transition for one texture to another is the result of agricultural practices on the plot during a year. The agricultural practices are the factors that modify the texture of the plots. In the present version of our model, we only implemented the dairy farming functioning. This choice is due to the fact that dairy farming is the most important activity of the studied areas (north of the Massif central). The model is based on the point of view of the breeder. The herd and its feeding are of great importance to the farmer’s decision process. We modelled two kinds of farming activities : the usual ones and exceptional ones. The usual ones are fodder production and herd grazing. To do that, the breeder must carefully choose the plots for each activity, according to production capacities of each plot. The second ones correspond to the agricultural system adaptations. The breeder can give up some plots, for example because of their lack of production capacities. He can also use new plots that he recently inserted in the agricultural system or that were unused for some time. These exceptional practices are essential in the Paysagri model. They represent the most important variations of area used by the agricultural systems. In our model, a special attribute named “landscape perception” is associated with each breeder. That’s why the breeder has a key role in his agricultural system changes. The “landscape perception” attribute guides the farmer’s choice concerning the exceptional practices. This attribute is an. S. Dépigny – Proposition de résumé pour le colloque SMAGET 2005 - 06/12/2004.

(4) original point of our model, because technical and economical facets of the farmers are not only aspects taken into account. The breeder’s feeling about his occupation, his living environment, his way of life… are numerous elements considered in the model. Public policies are the first cause of agricultural system changes. They influence the breeder’s strategy and the impact of the farming activities on landscape. Therefore, those policies often act indirectly on landscape. They are not included in the model, but there are outside factors that modify the behaviour of the model. To build Paysagri, we used an object oriented approach. Although our model is not a Multi Agent Model yet, our object-oriented approach will allow the implementation of agents as soon as it will be necessary. Presently, it is based on discrete event simulation method. We used the “Unified Modelling Language” to formalize the model. Then we chose the “Python” language for computer implementation, because it is a powerful object-oriented programming language with very clear syntax. Starting from a given landscape, the software performs simulations. Each year, it computes the choices of every breeder and their consequences on the territory. It produces a new landscape, which is the gathering of simulated plot textures. As an example, the simulation of 15 years, with 100 plots and 2 breeders takes about 3 minutes on a PIII 800 Mhz computer. We inserted the Paysagri model into a larger project that allows us to work with “Geographic Information System” data. We generate both maps or 3D realistic landscape images. We plan to use the data resulting from our model into two different ways. Firstly, we would like to use Paysagri as a research model. We think it could help to better understand the relationships between landscape production and agricultural system development. Secondly, results will be used as a basis for discussion in the frame of construction of shared territory projects. For example, our model could be used to put the emphasis on the farmer’s role in landscape evolution.. S. Dépigny – Proposition de résumé pour le colloque SMAGET 2005 - 06/12/2004.

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