scaling procedure, Fn is a non-linear function of the field area. For example, if Fn = 103 An-An2, when An <> 100 I ha-1, whereas if An > 3ha, Fn < total =" " n="1">4.3. Framework of hierarchy and scale an exampleTo cross the barrier of scale, a general framework: based upon the classical method of natural sciences, involving observation, hypothesis and test is proposed (Table 2). Within this framework, which here is posed for a simplified case that assumes one uniform decision-maker, specific linear, non-1inear or hierarchical scaling functions may be explored and used to support decision-making (Bierkens et al., 2000). In the following, an application of this simplified framework is illustrated with a simple example, with one group of decision-makers. However, in reality there are often many different actors, stakeholders and decision-makers in many hierarchies and scales, making application of the framework more complicated. In the present example, the criteria of the framework of hierarchy and scale are indicated with numbers in brackets. The targeted decision-makers were Danish politicians who after the Rio-Conference in 1992 demanded information on how agriculture could contribute to reduce the Danish energy use and greenhouse gas emissions by the promised 20%. Specifically, they wanted to know whether three different scenarios for conversion to organic farming might help to reduce the energy use (Bichel Committee, 1999). The time scale was a 12-year period (Danish Ministry of Environment and Energy, 1995), and the spatial scale was the 27,000 km2 agricultural area of Denmark (criteria 1 in Table 2). As the existing figures on energy use were sampled on the field and animal housing level (criteria 2), the question was how to upscale these data to the national level. The simplest option would have been a linear scaling procedure, where the average energy uses for different field crops and livestock housings is multiplied with national crop and livestock figures (criteria 3). However, because of scale dependent non-linearities and significant emerging factors, a linear scaling procedure was too simple for the upscaling (criteria 4). For reasons discussed in section a non-linear scaling procedure (criteria 3) was also too simple to predict fuel use (criteria 4), and a hierarchical scaling procedure was needed (criteria 3). In this case, a two-step application of the hierarchy-scale framework was tested. Step one was from the field to the farm level and step two was the final national level generalisation.4.3.1. Step oneMeasurements revealed a 47% deficiency in farm level fuel use compared to field level literature values linearly upscaled to the farm level (Refsgaard et al., 1998). and extended sampling on the field and farm level was initiated (criteria 4). A new model for calcu1ation of farm level fossil energy was made (Dalgaard et al, 2001) including fuel use as a function of the amount of inputs used, yield and the soil type on each field (criteria 3). Also, the above-mentioned emergent factors of fuel use for transport between fields and the farm and between the farm, fodder stocks and feedstuff businesses were included. Finally, the new model was verified (criteria 4) with samples