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The growing need for food due to a rapidly growing world population, especially in the developing countries leads in many cases to the intensive use of exploitative farming methods. Lacking alternatives rural agricultural farming systems adopted technologies which are nowadays realized to degrade their environment. Contaminated drinking water, acidification and salinization of the soil are the direct consequences of nonsustainable monocultural highly productive farming methods which depend on a huge input of pesticides and fertilizers. The degradation of the natural resource base is often noticed to come along with a decrease in biodiversity and a high input/output ratio. During the last decade there was a growing urge to develop indicators which can quantify ecological as well as economical soundness of agroecosystems and assess agroecosystem health. Farmers and researchers often have an intuitive idea that some farming methods are more sustainable than others, but putting new technologies into action often seems a risk prone venture.

Therefore a dynamic mathematical model FARMSIM is developed in order to take the first step towards a sophisticated farm management tool. The aim is to assess and quantify the impact of the introduction of new farm management strategies in advance. Modeling virtual farms with indigenous categories is thought to be a promising step towards supporting farmers to adopt more sustainable farming methods. Moreover, new sustainability indicators can be developed and tested to a wide range of conditions without time-consuming measurements. Increase in biodiversity and establishing synergistic effects between farm enterprises through recycling are being widely speculated to be important features of new sustainable agroecosystems. FARMSIM models the integration of various important farm enterprises through recycling resource flows. The most important modeled enterprises are a rice field with bundweeds, livestock such as buffalos, pigs and chickens and aquaculture.

After the development of the model concept which identified the most important stocks and flows on Philippine small-scale farms, the submodels with their respective input-output relationships were formulated and quantified. Each compartment is modeled according to data or model availability. The rice model as well as the livestock model are theoretical biophysical models which have been calibrated to Philippine conditions. The bundweeds, buffalo and fish pond models are developed on the basis of statistical relationships derived from various data sets from the Philippines.

After the implementation of the model and the definition of all potential resource flows a first analysis of the indicator 'efficiency' which determines the input-output ratio was conducted. Simulating three different scenarios it became obvious that our general perception of sustainability was supported by the model outcomes. The more enterprises were integrated into the farm and the more recycling of farm by-products was practiced the more efficient the farm became in terms of nitrogen. It was noticed that the potential for recycling or reusing farm by-products, like rice left-overs or livestock manure was large.

Aquaculture was also shown to have a large potential to improve sustainability on smallholder resource-poor rice farms in the tropics. It not only increases diversity on the farm but also does not depend on additional external inputs which in turn improves overall farm performance.

The true potential of the model FARMSIM lies in its capability to model a vast range of different farm scenarios and management strategies. A rapid appraisal of new farming methods can be conducted and once other features of tropical farming systems have been incorporated into FARMSIM, like economical levels and more enterprises, sustainability indicators can be developed and tested to a wide range of conditions together with the targeted farmers. Indigenous categories where the basis of the FARMSIM-concept so that farmers can anticipate in system design, hoping to find a way where high yields, sustaining soil fertility and environmental protection do not mutually exclude each other.