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FARMSIM: A dynamic model for the simulation of yields, nutrient cycling and resource flows on Philippine small-scale farming systems

by Joerg Schaber

1. INTRODUCTION


1.1 The Necessity of Integrated Resource Management (IRM)

In the middle of the 20th century, a rapidly growing world population, especially in the developing countries resulted, among other problems, in an increasing food demand. While the arable land was reduced because new housing areas were made accessible, the growing need for food in those regions, i.e. mostly rice, was basically met by two policies:

  1. development and introduction of new high yielding crop varieties and
  2. propagation of intensive agriculture.
Advances in biotechnologoy and agricultural research with the aim to meeting the increased food demand of the world and to fighting hunger was called the 'green revolution'. Doubtless, the 'green revolution' was very successful in the developing countries in the 1960s. At least for one generation hunger and poverty could be fought back in many regions. But evidence suggests that this approach will soon lose its impetus if it has not already been stopped (Ref. FAO). At the beginning of the next century China, India and Africa with each more than a billion people will not only call for sufficient food supply, but also claim the standard of living of the western world. This will prove difficult because, unfortunately, the 'green revolution' mostly came along with a homogenization of the agricultural landscape and intensive use of water, pesticides and chemical fertilizers. So it is often overseen that the 'green revolution' could only happen at the cost of degraded soils, contaminated drinking water and a high loss in biodiversity. Now we realize that the way we used the arable land could not sustain the natural resource base we depend on. Going on as before it will be impossible to produce food and wealth for an additional five to eight billion people on 'less arable land, with less water and less agrochemistry with prices that will be affordable also for the poor' (Lampe, Geo Nr. 11/96 p. 88).

Many of today's farming methods degrade the environment. In the developing countries persistent poverty forces farmers to adopt nonsustainable farming methods, e.g. slash and burn, whereas in the so-called developed countries highly productive monocultures result in degraded soils through acidification and salinization, e.g. soil degradation in the USA.
In the absence of alternatives, exploitative techniques will prevail.

Philippines

Farming methods in the Philippines also changed under the influence of the 'green revolution'. The need for high yields of rice mostly resulted in monocultural rice farms. Still, the population kept growing and nowadays the present farming system can hardly meet the farmers' demand for food and money. Certainly, present farming methods will not meet the projected demand for food and money in the next century, let alone the urge for environmental conservation.

It was oberserved that the long-term use of chemical fertilizers has a negative impact on the fertility of the topsoil. Fertilizers consist of up to 60 % so-called 'fillers', so that the nutrients contained in the fertilizer can be more easily broadcasted and spread out on the field. This filler mainly consists of pure sand, resulting in an application of tons of pure sand each year to the fields. So the soil becomes more and more sandy, thus losing its capability to hold water. More water is lost by evaporation and percolation followed by acidification and salinization.
Pesticides lose their benefits in the long run, pests become resistant, and the ground and drinking water becomes contaminated. The loss of biodiversity through monoculture walks along with the loss of the inherent ability of an ecosystem to heal itself and overcome or regulate exploding pest populations, like, e.g. golden snails in Philippine rice fields. In other words, it has been realized that intensive agriculture leads to a degradation of the natural resource base of agroecosystems.

These concerns also enabled international bodies like the Consultative Group on International Agricultural Research (CGIAR) to recognize the need for sustainable farming systems. It is the goal of agroecosystems research to find ways and means to quantify and assess the impact of different management strategies according to their ecological and economical soundness. In order to avoid the same mistakes that have been made in the past, it is not only important to measure and assess the productivity of agro-ecosystems, but also their ecological health and their ability to sustain and regenerate their natural resources. New ways of farming that regenerate the natural resource base must be developed, tested and put into operation by large numbers of small-scale farmers, hoping that high yields, sustaining soil fertility and environmental protection do not mutually exclude each other.

Basic features of such new Integrated Resource Management (IRM) will surely be biological diversification and nutrient recycling. Such approaches require 'system thinking'. Still rare, 'recent developments in Farming Systems Research (FSR), particularly in agroecosystems analysis, however, offer frameworks for scientists to see opportunities for intensifying resource use and regenerating diminished environments by integration of agriculture and aquaculture'(Lightfoot,1990).

1.2 Aquaculture as an example of IRM

Integrated farming systems, with aquaculture as a minor or major component of crop-livestock based farms differ greatly from extensive or intensive monocultural fish or rice farms. Stand alone enterprises with only one main product are risky ventures for resource-poor farmers in the developing countries, because they are strongly subdued to climatic, environmental and economical fluctuations (Lightfoot et al., 1993). Farmers who cultivate only rice, for instance, are threatened by starvation if their yield is destroyed by a typhoon, which are quite common not only in the Philippines. Moreover, as stated above, intensive rice monocultures with a high input of pesticides and fertilizers lead to a degradation of the soil in the long run. Therefore yields decrease, which is mostly regulated by the use of even more fertilizers. A positive feedback cycle is established and the situation becomes worse and worse. On the other hand, large fish farms have also often resulted in financial and environmental disasters because of environmental effects, e.g. pollution, and economic factors, such as volatility of prices (Cross, 1991).

Nonintensive aquaculture provides a way to use the wastes from other farm enterprises as an input to the fishpond, making small-scale farms more productive without additional external inputs. Waste such as animal manure, crop residues and crop by-products, weeds, tree leaves and kitchen left-overs become valuable resources, and fertilizers which were lost to the environment before. Fish convert plant and animal residues into high quality protein and enrich pond mud for use on the crop land which in turn has a potential of reducing commercial fertilizers with its adverse long-term effects. So the positive effect is two-folded. External inputs are reduced and at the same time the amount of primary farm products increase. Integrated farming systems that include semi-intensive aquaculture on a small-scale level are less risky ventures because they profit

  1. from the synergismn among farm enterprises making the whole system more efficient,
  2. from the diversity of produce making the farmers more independent from environmental and economical fluctuations, and
  3. from their environmental soundness by reducing high external inputs.
'In essence they are intensifying the use of land and water resources in a sustainable manner through species diversification and nutrient recycling' (Lightfoot, 1990).

Those rather theoretical arguments for IRM developed by various scientists in the last decade lead to the notion of aquaculture being the panacea of small-scale farmers suffering from poverty in the developing countries. Various experiments were conducted throughout the world where scientists tested the potential of numerous fish-livestock or fish-crop integration methods. The various combinations of fish with livestock and crops often performed impressively well on research stations (Edwards, 1983; Hopkins and Cruz, 1982). The transfer of these new approaches to on-farm situations often did not meet the desired effects. Most of these research projects were usually evaluated looking at the production and profitability of fish. By neglecting the 'system thinking' point of view the impacts of such strategies on the whole farm level was not analyzed. Therefore, such surely scientific and also important studies were only of limited use to the farmers themselves. Farmers are not docile acceptors of new technologies (Lightfoot et al., 1993). They possess a large indigenous knowledge of connections and correlations of the processes on the farm and its environment, including methods and technologies. Therefore, they also have a much better general understanding of what is feasible and what is not. They naturally look at the farm as a whole, also in the economical, social and political context. Agriculture in those regions of the Philippines is prone to be a risky undertaking, so they understandably are very careful in adopting new ventures like aquaculture. Scientists, on the other hand, might be more aware of the fact that it just cannot go on as usual and that new ideas and technologies must be urgently put into action if farmers want to sustain their environment for the next generation. Therefore scientists and farmers must work together. Farmers must participate in system design.

1.3 The Participatory Research Appraisal - The RESTORE-Project

The IRM approach integrates the management of new farm enterprises, especially aquaculture, with existing farming systems and their natural resource base in order to use the potential of rehabilitation by establishing synergistic effects among farm enterprises and their environment. This approach involves interdisciplinary studies and close collaboration of the targeted farmers. Integration of farm enterprises and mechanisms to improve natural resource management can only be encouraged and realized if researchers can find procedures that will be used by farmers. By introducing farmers to system thinking, indigenous categories build the foundation of the partnership of farmers and scientists. In fact, indigenous categories serve as an entry point towards IRM (Lightfoot et al., 1993).

The International Center for Living Aquatic Resource Management (ICARLM) has developed methods to help farmers to identify and map indigenous categories of their own natural resource system, i.e. the farm. Drawing diagrams such as village transects and bioresource flow models (Fig.1) together with the farmers build the starting point of understanding system behavior and developing an analytical framework for those categories for both farmers and scientists. Those diagrams become the core of sharing information, experience and ideas on how to rehabilitate the natural resource base and to integrate new farm enterprises such as aquaculture, agroforestry and vegetable gardening into working farming systems (Lightfoot et al.,1993).


Fig. 1: Before and after Integation: bioresource flows between resource systems, Philippines. Source : ICLARM, Manila

The International Center for Living Aquatic Resource Management (ICARLM) has developed methods to help farmers to identify and map indigenous categories of their own natural resource system, i.e. the farm. Drawing diagrams such as village transects and bioresource flow models (Fig.1) together with the farmers build the starting point of understanding system behavior and developing an analytical framework for those categories for both farmers and scientists. Those diagrams become the core of sharing information, experience and ideas on how to rehabilitate the natural resource base and to integrate new farm enterprises such as aquaculture, agroforestry and vegetable gardening into working farming systems (Lightfoot et al.,1993).

The single parameters evolve dynamically over the years due to seasonal differences and climatic changes. But they also reveal a general trend towards better overall farm performance through increased IRM. Productivity increases and farmers' incomes rise. The snapshots mapped on a kite-diagram serve as an experimental tool to compare different farming systems across time and space. The larger the kite, the better the farm performance. This approach helps both farmers and researchers to shift their view and focus from the individual farm enterprise to the entire environment towards realizing the benefits of managing the natural resources in an integrated and sustainable manner. Making efficient use of available biological material and resources is a result of adopting 'system thinking'.

1.4 Models of Integrated Farming Systems

Those experiments and projects with farmers in the Philippines suggest that the IRM approach is promising. As the number of farmers adopting the new ideas of IRM grows, the numbers that really affect the environment grow as well. When farmers report that the use of compost made of farm, animal waste and crop by-products reduce the need for inorganic fertilizers by 50 % (conversations with farmers), the absolute amounts might seem small, but as more and more farmers shift towards IRM those numbers become significant for the whole region. Monitoring of sustainability parameters shows that farming systems can be transformed rapidly. But the question arises of whether those parameters are the only ones or the right ones?


Fig. 2: Time series performance indicators by season, Philippines. Source: Lightfoot et al. (1993)

The rather simplistic approach of merely counting the number of recycling flows and species must take into account the absolute quantities as well. How can ecosystem attributes like resilience and maturity be calculated? We all have an intuitive perception of how a natural environment is managed in a sustainable way, but more direct indicators of the quality of an ecosystem must be found. The most sustainable way an ecosystem is managed, of course, is not to intervene at all in the natural processes. Nevertheless, we have to if we want to produce food for the whole population. Therefore scientific procedures for quantifying, analyzing and experimenting with farming systems of this complexity are badly needed. One procedure is the use of ecological modeling tools like ECOPATH II (Christensen and Pauly, 1992; Dalsgaard, 1996). ECOPATH is a software tool which can be used to implement static mass-balance equation which gives us the opportunity to analyze flows and storages in the steady state. This nondynamic approach is useful for describing and generating average pictures or 'snapshots' of the state of complex ecosystems (Joergensen, 1994).


Fig. 3: Farming system performance indicators kites before and after integration, Philippines. Source: Lightfoot at al. (1993)

For taking real snapshots, data availability and time intensive monitoring might be a constraint on the wider adoption of this framework (Dalsgaard, 1996). Looking at the average picture might also conceal important information about farm performance in the changing system. Seasonality and different farm management strategies within short periods of time could have an important impact on overall sustainability. Looking at the steady state, this information is lost.

Scope of this thesis

Therefore it is the goal of the project 'Development of Sustainability Indicators for Integrated Agriculture-Aquaculture Farming Systems' and of this thesis to formulate a dynamic model as a future farm management tool on the basis of existing knowledge. The aim is to identify and quantify the dynamic relations of potential farm enterprises and resources, so that any number of snapshots and average pictures can be taken and analyzed without time intensive monitoring. Then quantitative analysis and synthesis can be performed taking into account farmers' participatory flow modeling. One important feature of a dynamic farm model will be the rapid assessment of the impact of new management strategies under a wide range of conditions. Presently, little knowledge exists as to the accuracy, the stability and responsiveness of sustainability indicators towards different conditions, such as farm size, farm types, cropping patterns, seasonality, etc. With a dynamic model detailed studies concerning these features can be conducted. Developing and applying a dynamic model also shifts the focus from the productivity and performance of single farm enterprises towards the whole farm level. That means that for the first time the conception of a farm as a whole is supported interactively. Users can actually train their 'system thinking' by studying effects of different management strategies within seconds. Researchers mostly biased towards their leading discipline can practice looking at the whole farm with the effect that they start thinking within the same categories as the farmers themselves. Now collaboration between farmers and scientists can carry fruits in the way that scientists can develop and test farming alternatives that are more likely to be adopted, because they take into account the economical and ecological soundness of the whole farm. Then we will see whether high yields, sustaining soil fertility and environmental protection do mutually exclude each other or not. The use of dynamic ecosystem modeling will help to develop an agroecological sustainability index which reflects the grade of the sustainable use of natural resources. This will show farmers throughout the world alternatives to use their natural resource base in a manner that coming generations can profit from the natural resource base as well. Working towards this aim seems to be the only alternative for resource-poor farmers in the developing countries.

The following description of the dynamic farm model FARMSIM is the first step towards the perspective of the derivation of an agroecological sustainability index and a future farm management tool for the rapid assessment of different farm management strategies concerning their ecological and economical soundness.



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