Im Okologischen Landbau gewinnt die Fruchtfolgegestaltung als wesentlicher Aspekt der strategisch... more Im Okologischen Landbau gewinnt die Fruchtfolgegestaltung als wesentlicher Aspekt der strategischen und taktischen Planungsebene im Ackerbau durch den Verzicht auf externe Steuermechanismen gegenuber der operativen Planungsebene (z.B. Pflanzenschutzmitteleinsatz nach Prognosemodellen) an relativer Bedeutung. Deshalb ist die Entwicklung eines Entscheidungsunterstutzungsmodells zur Fruchtfolge-Planung (fur die Bereiche N-Versorgung, Beikrautregulierung, Berucksichtigung phytosanitarer Restriktionen) gerade zur Optimierung des okologischen Landbaus sinnvoll.
... predictions are needed of the degree of goal achievement over the policy planning horizon giv... more ... predictions are needed of the degree of goal achievement over the policy planning horizon given the ... it is more likely that results feed back to the definitions of indicator set or system ... included peer-reviewed journals, 'grey' literature in reports often in local language, and websites ...
The aim of this chapter is to present a bio-economic modelling framework established to provide i... more The aim of this chapter is to present a bio-economic modelling framework established to provide insight into the complex nature of agricultural systems and to assess the impacts of agricultural and environmental policies and technological innovations. This framework consists of a Farm System Simulator (FSSIM) using mathematical programming that can be linked to a cropping system model to estimate at field level the engineering production and environmental functions. FSSIM includes a module for agricultural management (FSSIM-AM) and a mathematical programming model (FSSIM-MP). FSSIM-AM aims to define current and alternative activities and to quantify their input output coefficients (both yields and environmental effects) using a cropping system model, such as APES (Agricultural Production and Externalities Simulator) and other sources (expert knowledge, surveys, etc.). FSSIM-MP seeks to describe the behaviour of the farmer given a set of biophysical, socio-economic and policy constraints and to predict its reactions under new technologies, policy and market changes. The communication between these different tools and models is based on explicit definitions of spatial scales and software for model integration. The bio-economic modelling framework was designed to be sufficiently generic and flexible in order to be applied for all relevant farming systems across the European Union, easily transferable between different geographic locations, and reusable for different applications. For this chapter, it was tested for a set of farms representing the arable farming systems in two European regions (Flevoland [Netherlands] and Midi-Pyrénées [France]) in order to analyse the current situation and anticipate the impact of new alternative scenarios.
Im Okologischen Landbau gewinnt die Fruchtfolgegestaltung als wesentlicher Aspekt der strategisch... more Im Okologischen Landbau gewinnt die Fruchtfolgegestaltung als wesentlicher Aspekt der strategischen und taktischen Planungsebene im Ackerbau durch den Verzicht auf externe Steuermechanismen gegenuber der operativen Planungsebene (z.B. Pflanzenschutzmitteleinsatz nach Prognosemodellen) an relativer Bedeutung. Deshalb ist die Entwicklung eines Entscheidungsunterstutzungsmodells zur Fruchtfolge-Planung (fur die Bereiche N-Versorgung, Beikrautregulierung, Berucksichtigung phytosanitarer Restriktionen) gerade zur Optimierung des okologischen Landbaus sinnvoll.
... predictions are needed of the degree of goal achievement over the policy planning horizon giv... more ... predictions are needed of the degree of goal achievement over the policy planning horizon given the ... it is more likely that results feed back to the definitions of indicator set or system ... included peer-reviewed journals, 'grey' literature in reports often in local language, and websites ...
The aim of this chapter is to present a bio-economic modelling framework established to provide i... more The aim of this chapter is to present a bio-economic modelling framework established to provide insight into the complex nature of agricultural systems and to assess the impacts of agricultural and environmental policies and technological innovations. This framework consists of a Farm System Simulator (FSSIM) using mathematical programming that can be linked to a cropping system model to estimate at field level the engineering production and environmental functions. FSSIM includes a module for agricultural management (FSSIM-AM) and a mathematical programming model (FSSIM-MP). FSSIM-AM aims to define current and alternative activities and to quantify their input output coefficients (both yields and environmental effects) using a cropping system model, such as APES (Agricultural Production and Externalities Simulator) and other sources (expert knowledge, surveys, etc.). FSSIM-MP seeks to describe the behaviour of the farmer given a set of biophysical, socio-economic and policy constraints and to predict its reactions under new technologies, policy and market changes. The communication between these different tools and models is based on explicit definitions of spatial scales and software for model integration. The bio-economic modelling framework was designed to be sufficiently generic and flexible in order to be applied for all relevant farming systems across the European Union, easily transferable between different geographic locations, and reusable for different applications. For this chapter, it was tested for a set of farms representing the arable farming systems in two European regions (Flevoland [Netherlands] and Midi-Pyrénées [France]) in order to analyse the current situation and anticipate the impact of new alternative scenarios.
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Papers by Peter Zander