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To improve agriculture faced with regional sustainability issues, agricultural landscapes providing a diversity and high level of ecosystem services are necessary. We have developed and tested the MOSAICA-f framework to build innovative multi-functional agricultural landscapes that can consider explicitly: 1) the performance of cropping systems at the field scale, 2) farmers' decision processes on the adoption of cropping systems, and 3) possible scenarios for innovations and policy changes at the regional scale. This framework is based on a scenario approach that encompasses normative, exploratory and optimized scenarios to assess the relevance of combinations of new agricultural policies, changes to the external context (market and regulations) and innovations in cropping systems. The impacts of these changes on sustainability issues are simulated using the regional bioeconomic model MOSAICA for farmers' decision processes regarding the adoption of cropping systems at the field scale throughout a region. Applied in Guadeloupe (French West Indies), the MOSAICA-f framework enabled the design of a scenario increasing agricultural added value, food and energy self-sufficiency, employment and the quality of water bodies and reducing greenhouse gas emissions. This sustainable scenario combines new cropping systems tuned to farm types with a reorientation of subsidies, an increased workforce and banning food crop production on polluted soils. It can be used to understand the potential contribution of agriculture to sustainability issues and to help local decision makers define policies that will account for the spatial diversities of farms and fields in a landscape. Beyond the design of such a win-win scenario, MOSAICA-f has revealed trade-offs in the provision of services by agriculture.

Workshop 6.4 Integrated simulation modeling in farming system research ; Models are common tools used for scenario assessment of agricultural systems. In this paper we present the combined application of three modeling approaches for participatory integrated assessment of scenarios for agriculture in the Camargue area (South of France). By means of a land use change analysis (LUC), an agent-based model (ABM), and a bio-economic model (BEM), we assessed with farmers and other stakeholders of the area scenarios related to the CAP reform and the possible extension of alternative, more environmentally friendly, farming systems. The LUC analysis was used as a tool to characterize, from a retrospective point of view, the capacity for change of farming systems. By identifying and measuring the main biophysical constraints and actual socio-economic situation, we were able to initiate the discussion with farmers and other stakeholders inside the Camargue region. The ABM has proved to be a powerful tool to organize and focus the collective discussions on possible adaptation strategies of farming systems. Finally the use of the BEM helped to discuss with stakeholders some plausible and desired scenarios for agricultural systems in the region. The combined application of the three modeling approaches is embedded in a more general framework for Prospective and Participatory Integrated Assessment of Agricultural Systems (PIAAS). In PIAAS, stakeholders play a central role in the definition of scenarios and indicators for their evaluation, the co-development of models, and their use for scenario assessment. Specific results for scenarios related to different subsidies levels for rice under the CAP reform and the reduction of pesticide use are presented as well as the evaluation of the whole framework by local stakeholders.

Workshop 6.4 Integrated simulation modeling in farming system research ; Models are common tools used for scenario assessment of agricultural systems. In this paper we present the combined application of three modeling approaches for participatory integrated assessment of scenarios for agriculture in the Camargue area (South of France). By means of a land use change analysis (LUC), an agent-based model (ABM), and a bio-economic model (BEM), we assessed with farmers and other stakeholders of the area scenarios related to the CAP reform and the possible extension of alternative, more environmentally friendly, farming systems. The LUC analysis was used as a tool to characterize, from a retrospective point of view, the capacity for change of farming systems. By identifying and measuring the main biophysical constraints and actual socio-economic situation, we were able to initiate the discussion with farmers and other stakeholders inside the Camargue region. The ABM has proved to be a powerful tool to organize and focus the collective discussions on possible adaptation strategies of farming systems. Finally the use of the BEM helped to discuss with stakeholders some plausible and desired scenarios for agricultural systems in the region. The combined application of the three modeling approaches is embedded in a more general framework for Prospective and Participatory Integrated Assessment of Agricultural Systems (PIAAS). In PIAAS, stakeholders play a central role in the definition of scenarios and indicators for their evaluation, the co-development of models, and their use for scenario assessment. Specific results for scenarios related to different subsidies levels for rice under the CAP reform and the reduction of pesticide use are presented as well as the evaluation of the whole framework by local stakeholders.

Models are common tools used for scenario assessment of agricultural systems. In this paper we present the combined application of three modeling approaches for participatory integrated assessment of scenarios for agriculture in the Camargue area (South of France). By means of a land use change analysis (LUC), an agent-based model (ABM), and a bio-economic model (BEM), we assessed with farmers and other stakeholders of the area scenarios related to the CAP reform and the possible extension of alternative, more environmentally friendly, farming systems. The LUC analysis was used as a tool to characterize, from a retrospective point of view, the capacity for change of farming systems. By identifying and measuring the main biophysical constraints and actual socio-economic situation, we were able to initiate the discussion with farmers and other stakeholders inside the Camargue region. The ABM has proved to be a powerful tool to organize and focus the collective discussions on possible adaptation strategies of farming systems. Finally the use of the BEM helped to discuss with stakeholders some plausible and desired scenarios for agricultural systems in the region. The combined application of the three modeling approaches is embedded in a more general framework for Prospective and Participatory Integrated Assessment of Agricultural Systems (PIAAS). In PIAAS, stakeholders play a central role in the definition of scenarios and indicators for their evaluation, the co-development of models, and their use for scenario assessment. Specific results for scenarios related to different subsidies levels for rice under the CAP reform and the reduction of pesticide use are presented as well as the evaluation of the whole framework by local stakeholders.

The rapid evolution of economie and environmental constraints on farming systems require cropping systems design or assessment to be conducted in the context of market instability as well as economie (c.g. CAP in EU) and environmental policy changes. The Nitrate Directive (91/676/EC) is one of the oIdest EU environmental policy, designed to reduce water pollution by nitrate from agricultural sources, through a set of measures, defined at regional level, and mandatory for farmers of vulnerable zones

UMR SYSTEM : équipe AMPLUS ; To improve agriculture faced with regional sustainability issues, agricultural landscapes providing a diversity and high level of ecosystem services are necessary. We have developed and tested the MOSAICA-f framework to build innovative multi-functional agricultural landscapes that can consider explicitly: 1) the performance of cropping systems at the field scale, 2) farmers' decision processes on the adoption of cropping systems, and 3) possible scenarios for innovations and policy changes at the regional scale. This framework is based on a scenario approach that encompasses normative, exploratory and optimized scenarios to assess the relevance of combinations of new agricultural policies, changes to the external context (market and regulations) and innovations in cropping systems. The impacts of these changes on sustainability issues are simulated using the regional bioeconomic model MOSAICA for farmers' decision processes regarding the adoption of cropping systems at the field scale throughout a region. Applied in Guadeloupe (French West Indies), the MOSAICA-f framework enabled the design of a scenario increasing agricultural added value, food and energy self-sufficiency, employment and the quality of water bodies and reducing greenhouse gas emissions. This sustainable scenario combines new cropping systems tuned to farm types with a reorientation of subsidies, an increased workforce and banning food crop production on polluted soils. It can be used to understand the potential contribution of agriculture to sustainability issues and to help local decision makers define policies that will account for the spatial diversities of farms and fields in a landscape. Beyond the design of such a win-win scenario, MOSAICA-f has revealed trade-offs in the provision of services by agriculture.

UMR SYSTEM : équipe AMPLUS ; To improve agriculture faced with regional sustainability issues, agricultural landscapes providing a diversity and high level of ecosystem services are necessary. We have developed and tested the MOSAICA-f framework to build innovative multi-functional agricultural landscapes that can consider explicitly: 1) the performance of cropping systems at the field scale, 2) farmers' decision processes on the adoption of cropping systems, and 3) possible scenarios for innovations and policy changes at the regional scale. This framework is based on a scenario approach that encompasses normative, exploratory and optimized scenarios to assess the relevance of combinations of new agricultural policies, changes to the external context (market and regulations) and innovations in cropping systems. The impacts of these changes on sustainability issues are simulated using the regional bioeconomic model MOSAICA for farmers' decision processes regarding the adoption of cropping systems at the field scale throughout a region. Applied in Guadeloupe (French West Indies), the MOSAICA-f framework enabled the design of a scenario increasing agricultural added value, food and energy self-sufficiency, employment and the quality of water bodies and reducing greenhouse gas emissions. This sustainable scenario combines new cropping systems tuned to farm types with a reorientation of subsidies, an increased workforce and banning food crop production on polluted soils. It can be used to understand the potential contribution of agriculture to sustainability issues and to help local decision makers define policies that will account for the spatial diversities of farms and fields in a landscape. Beyond the design of such a win-win scenario, MOSAICA-f has revealed trade-offs in the provision of services by agriculture.

UMR SYSTEM : équipe AMPLUS ; To improve agriculture faced with regional sustainability issues, agricultural landscapes providing a diversity and high level of ecosystem services are necessary. We have developed and tested the MOSAICA-f framework to build innovative multi-functional agricultural landscapes that can consider explicitly: 1) the performance of cropping systems at the field scale, 2) farmers' decision processes on the adoption of cropping systems, and 3) possible scenarios for innovations and policy changes at the regional scale. This framework is based on a scenario approach that encompasses normative, exploratory and optimized scenarios to assess the relevance of combinations of new agricultural policies, changes to the external context (market and regulations) and innovations in cropping systems. The impacts of these changes on sustainability issues are simulated using the regional bioeconomic model MOSAICA for farmers' decision processes regarding the adoption of cropping systems at the field scale throughout a region. Applied in Guadeloupe (French West Indies), the MOSAICA-f framework enabled the design of a scenario increasing agricultural added value, food and energy self-sufficiency, employment and the quality of water bodies and reducing greenhouse gas emissions. This sustainable scenario combines new cropping systems tuned to farm types with a reorientation of subsidies, an increased workforce and banning food crop production on polluted soils. It can be used to understand the potential contribution of agriculture to sustainability issues and to help local decision makers define policies that will account for the spatial diversities of farms and fields in a landscape. Beyond the design of such a win-win scenario, MOSAICA-f has revealed trade-offs in the provision of services by agriculture.

International audience ; Cropping system models are widely used tools for simulating the growth and development of crops at field scale. However, it is often difficult to satisfy their detailed input and output data requirements for a proper evaluation of model. In this study, expert knowledge data were used as alternative source to fulfill these data requirements. The model was first calibrated for major crops of the studied area and then evaluated for the same crops by using expert knowledge data. Results showed that the model accurately simulated above-ground biomass and grain yield with a relative root mean square error (RRMSE) of 20 and 17%, respectively. On the other hand, simulated results were less satisfactory for N uptake and cumulated evapotranspiration with RRMSE of 27% and 31%, respectively. The model simulated cumulative variables more accurately than dynamic variables. The results of this study suggest that expert knowledge can be used to get data for intermediate variables rarely measured in experiments used for calibration (green LAI, actual evapotranspiration, rooting depth) in typical crop management conditions in the region. This approach enables a global and dynamic evaluation of cropping system models when experimental data is unavailable for large heterogeneous areas in a region.

International audience ; Cropping system models are widely used tools for simulating the growth and development of crops at field scale. However, it is often difficult to satisfy their detailed input and output data requirements for a proper evaluation of model. In this study, expert knowledge data were used as alternative source to fulfill these data requirements. The model was first calibrated for major crops of the studied area and then evaluated for the same crops by using expert knowledge data. Results showed that the model accurately simulated above-ground biomass and grain yield with a relative root mean square error (RRMSE) of 20 and 17%, respectively. On the other hand, simulated results were less satisfactory for N uptake and cumulated evapotranspiration with RRMSE of 27% and 31%, respectively. The model simulated cumulative variables more accurately than dynamic variables. The results of this study suggest that expert knowledge can be used to get data for intermediate variables rarely measured in experiments used for calibration (green LAI, actual evapotranspiration, rooting depth) in typical crop management conditions in the region. This approach enables a global and dynamic evaluation of cropping system models when experimental data is unavailable for large heterogeneous areas in a region.

International audience ; Cropping system models are widely used tools for simulating the growth and development of crops at field scale. However, it is often difficult to satisfy their detailed input and output data requirements for a proper evaluation of model. In this study, expert knowledge data were used as alternative source to fulfill these data requirements. The model was first calibrated for major crops of the studied area and then evaluated for the same crops by using expert knowledge data. Results showed that the model accurately simulated above-ground biomass and grain yield with a relative root mean square error (RRMSE) of 20 and 17%, respectively. On the other hand, simulated results were less satisfactory for N uptake and cumulated evapotranspiration with RRMSE of 27% and 31%, respectively. The model simulated cumulative variables more accurately than dynamic variables. The results of this study suggest that expert knowledge can be used to get data for intermediate variables rarely measured in experiments used for calibration (green LAI, actual evapotranspiration, rooting depth) in typical crop management conditions in the region. This approach enables a global and dynamic evaluation of cropping system models when experimental data is unavailable for large heterogeneous areas in a region.

International audience Cropping system models are widely used tools for simulating the growth and development of crops at field scale. However, it is often difficult to satisfy their detailed input and output data requirements for a proper evaluation of model. In this study, expert knowledge data were used as alternative source to fulfill these data requirements. The model was first calibrated for major crops of the studied area and then evaluated for the same crops by using expert knowledge data. Results showed that the model accurately simulated above-ground biomass and grain yield with a relative root mean square error (RRMSE) of 20 and 17%, respectively. On the other hand, simulated results were less satisfactory for N uptake and cumulated evapotranspiration with RRMSE of 27% and 31%, respectively. The model simulated cumulative variables more accurately than dynamic variables. The results of this study suggest that expert knowledge can be used to get data for intermediate variables rarely measured in experiments used for calibration (green LAI, actual evapotranspiration, rooting depth) in typical crop management conditions in the region. This approach enables a global and dynamic evaluation of cropping system models when experimental data is unavailable for large heterogeneous areas in a region.

Correspondance: wery@supagro.inra.fr ; International audience ; Introduction : Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of cropping and farming systems and to enhance their contributions to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired impacts could be greatly enhanced if the quality oftheir ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union have been defined (Van I.ttersum et al., 2008): (a) overcome the gap between micro-macro level analysis, (b) decrease the bias in integrated assessments towards either economic or environmental issues, (c) ensure reusability of models and their use for indicator assessment and (d) overcome hindrances in technical linkage of models. Tools for: integrated assessment must have multi-scale capabilities and preferably allow application to a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the design of a framework for agricultural systems (SEAMLESS Integrated Fratnework) and discusses the implications for cropping and farming systems modelling.

Correspondance: wery@supagro.inra.fr ; International audience ; Introduction : Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of cropping and farming systems and to enhance their contributions to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired impacts could be greatly enhanced if the quality oftheir ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union have been defined (Van I.ttersum et al., 2008): (a) overcome the gap between micro-macro level analysis, (b) decrease the bias in integrated assessments towards either economic or environmental issues, (c) ensure reusability of models and their use for indicator assessment and (d) overcome hindrances in technical linkage of models. Tools for: integrated assessment must have multi-scale capabilities and preferably allow application to a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the design of a framework for agricultural systems (SEAMLESS Integrated Fratnework) and discusses the implications for cropping and farming systems modelling.

Introduction : Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of cropping and farming systems and to enhance their contributions to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired impacts could be greatly enhanced if the quality oftheir ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union have been defined (Van I.ttersum et al., 2008): (a) overcome the gap between micro-macro level analysis, (b) decrease the bias in integrated assessments towards either economic or environmental issues, (c) ensure reusability of models and their use for indicator assessment and (d) overcome hindrances in technical linkage of models. Tools for: integrated assessment must have multi-scale capabilities and preferably allow application to a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the design of a framework for agricultural systems (SEAMLESS Integrated Fratnework) and discusses the implications for cropping and farming systems modelling.