Combining farmers' decision rules and landscape stochastic regularities for landscape modelling
Identifieur interne : 000122 ( PascalFrancis/Corpus ); précédent : 000121; suivant : 000123Combining farmers' decision rules and landscape stochastic regularities for landscape modelling
Auteurs : Noemie Schaller ; El Ghali Lazrak ; Philippe Martin ; Jean-François Mari ; Christine Aubry ; Marc BenoitSource :
- Landscape ecology [ 0921-2973 ] ; 2012.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
Landscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called "landscape agronomy", aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
pA |
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Format Inist (serveur)
NO : | PASCAL 12-0134688 INIST |
---|---|
ET : | Combining farmers' decision rules and landscape stochastic regularities for landscape modelling |
AU : | SCHALLER (Noemie); GHALI LAZRAK (El); MARTIN (Philippe); MARI (Jean-François); AUBRY (Christine); BENOIT (Marc) |
AF : | AgroParisTech, INRA, UMR 1048 SAD-APT, Batiment EGER, BP 01/78 850 Thiverval-Grignon/France (1 aut., 3 aut., 5 aut.); INRA, UR 055 SAD ASTER/88500 Mirecourt/France (2 aut., 6 aut.); LORIA, UMR CNRS 7503 INRIA-Grand-Est, B.P. 239/54506 Vandœuvre-lès-Nancy/France (4 aut.) |
DT : | Publication en série; Niveau analytique |
SO : | Landscape ecology; ISSN 0921-2973; Pays-Bas; Da. 2012; Vol. 27; No. 3; Pp. 433-446; Bibl. 2 p. |
LA : | Anglais |
EA : | Landscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called "landscape agronomy", aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology. |
CC : | 002A14D01; 002A14A02 |
FD : | Agriculteur; Règle décision; Paysage; Modélisation; Occupation sol; Dynamique; Modèle; Fouille donnée; Ecologie paysage |
ED : | Farmer; Decision rule; Landscape; Modeling; Land use; Dynamics; Models; Data mining |
SD : | Agricultor; Regla decisión; Paisaje; Modelización; Ocupación terreno; Dinámica; Modelo; Busca dato |
LO : | INIST-26279.354000502852540100 |
ID : | 12-0134688 |
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Pascal:12-0134688Le document en format XML
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<front><div type="abstract" xml:lang="en">Landscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called "landscape agronomy", aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.</div>
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<EA>Landscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called "landscape agronomy", aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.</EA>
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