Farm-SAFE: the process of developing a plot- and farm-scale model of arable,forestry, and silvoarable economics |
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Authors: | A R Graves P J Burgess F Liagre J-P Terreaux T Borrel C Dupraz J Palma F Herzog |
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Institution: | 1.Cranfield University,Cranfield,UK;2.Assemblée Permanente des Chambres d’Agriculture,Paris,France;3.Cemagref, 361, Rue J. F. Breton,Montpellier Cedex 5,France;4.Institut National de la Recherche Agronomique,Montpellier,France;5.Technical University of Lisbon,Lisboa,Portugal;6.Agroscope Reckenholz-T?nikon Research Station ART,Zurich,Switzerland |
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Abstract: | Financial feasibility and financial return are two key issues that farmers and land owners consider when deciding between
alternative land uses such as arable farming, forestry and agroforestry. Moreover regional variations in yields, prices and
government grants mean that the relative revenue and cost of such systems can vary substantially within Europe. To aid our
understanding of these variations, the European Commission sponsored a research project called “Silvoarable Agroforestry For
Europe” (SAFE). This paper describes the process of developing a new economic model within that project. The initial stages
included establishing criteria for the model with end-users and reviewing the literature and existing models. This indicated
that the economic model needed to allow comparison of arable farming, forestry and agroforestry systems at a plot- and a farm-scale.
The form of comparisons included net margins, net present values, infinite net present values, equivalent annual values, and
labour requirements. It was decided that the model would operate in a spreadsheet format, and the effect of phased planting
patterns would be included at a farm-scale. Following initial development, additional user feedback led to a final choice
on a model name, a final method of collating input data, and the inclusion of field-based operations such as varying the cropped
area, replacing dead trees, and pruning. In addition options in terms of improved graphical outputs and the ability to undertake
sensitivity analysis were developed. Some of the key lessons learnt include the need to establish clear model criteria and
the benefits of developing a working prototype at an early stage to gain user-feedback. |
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