CONCEPTUALISATION
The application of systems appraisal to agriculture and its graphic representation has never been easy as the multifaceted nature of its interdependent constituents interact in so many ways.
The rationalisation of farming systems generally, through the use for example, of simple crop nutrient requirements and the specialisation of enterprises has made a much simpler picture where comparative cost benefits can be assessed, but by its very nature it has already eliminated many of the benefits, and is faced with ever increasing costs through the establishment of direct linkages between those aspects of the farming situation that it is concerned with, and therefore making the complimentary character of many associations redundant, and therefore destroying fundamental links in the productive chain, and consequently fails to conceptualise the wider implications of these disturbances within the biological cycle (FIG.29).
Inputs come to represent a shopping list as the regenerative capacity of the land is diminished, whilst outputs market orientated destination can only ever be reinforced by the cost of these increasingly unproductive factors.
MODELS OF AGRICULTURAL DEVELOPMENT
From the farmers point of view there is no consensus over the best way to farm, all styles of farming can be seen as legitimate, and can hold sufficient future potential if
the farmers own input is seen as competent, but the main point for debate and conflict is the development of the “interface” with the interest of the state.
In this sense farmers are concerned with what type of farmer will dovetail best with state policy, and it is through trends in this direction that state preferred “optimal farming practises” are most visible (Van Der Ploeg 1990) (FIG.30).
The state agencies tend to be more involved with the incorporation of external influences into agricultural decision making, echoing principles of technocentrism and mainstream economic analysis of farm enterprises. Which bears out the projected and sometimes inflated influence of external parameters such as market expansion, unit cost reduction and technological progress.
This can be seen within models of technological innovation diffusion, which concentrate on adoption trends within categorised farmer groups and represent the degree of the incorporation into the farming community of chosen technologies (Bowler 1992).
Such classification schemes provide grids of resource allocation among different farm types with the large scale, highly intensified enterprise seen as the most innovative, and thus assuming the role of the “vanguard farm”, which subsequently becomes the optimal model in the eyes of the farmer (Van Der Ploeg 1990. Edwards 1992) By the use of such classification systems state agencies and agri-business groups make available resources to achieve successful promotion of their chosen patterns or styles of farming.
Such models of innovation diffusion can then be seen in a socio-political context, and claim to illustrate specific distributions of potential (competence, cultural factors, economic restrictions etc). This undeniably has a significant effect on our view of agricultural development, as it promotes the concept of a unilinear growth path on which those farming systems not intensified (due to some obstacle) are yet to intensify, and those where modernisation can be seen at odds with the production process, are viewed as archaic remnants of the past (FIG.3 1).
This is not to imply that structurally determined classification patterns have a universal effect on outcome, or that at the farmer level such concepts are universally believed, the search for new strategies, reactions and modifications emerge out of any existing style of farming, and this in many instances can be seen as a strong tendency within those areas considered, from a structural perspective, most negatively effected or marginalised, due in part to their high degree of self provision and therefore increased societal and developmental freedom.
The distance of such groups from the highly incorporated “vanguard” model, and their greater independence from state and agri-business technologies, allows deconstruction of the optimal model and the salvaging from it that which conforms to the farmers preferred methods, and the ability for this inversion exists on any level of farm decision making.
The major complication comes when technological science produces flows of information attempting to incorporate economic, institutional and technological factors into farm enterprise development. The ignorance this shows of farming experience makes it a coercive force, linked directly or indirectly to specific interests, delegitamising the farmer as the holder of wisdom and presenting new practises in such a way as to show them to be correct in a scientific sense; with the result that other methods – even the farmers own, are seen as dubious.
The destructive nature of this tendency can only be magnified by its adoption by developmental agencies such as the EEC.
DECISION MAKING PROCESSES
Despite the rationalisation of farming management, decisions are still made by individuals in response to their own perceptions of needs or consequences. This can be seen as largely due to the particular farmer being confident of his decision making and its consequences within the confines of his specific location, due to his experience of its functioning.
Unfortunately these processes which govern farming decision making are seldom available for accumulation, quantification and scientific analysis. Management decisions that may appear consistent in effect may be made for a multitude of reasons, thus any changes occurring as a result of these decisions are the net effects of many different and often conflicting actions.
Also trends that can be compared on similar timescales can often nevertheless be seen as causally unrelated due, for example, to the many effects of certain variable factors such as temperature, over a wide spectrum within the farming system. This exemplifies how easily spurious correlations can lead to false interpretations and the difficulty of drawing definitive conclusions from occurrences that may be the result of any number of unmeasurable processes that form the farmers experience.
This is not to suggest that wider influences on the farming process are irrelevant, management decisions themselves have shown to be largely effected by economic considerations (Lewis 1991). It is however, important to emphasise how impacts upon the environment operate through the actions of the farmer, who depends upon internal (phycological) and external (economic social etc) influences.
As has been shown one of the most important of these external influences has been government policy and associated government sponsored advise.
To a large extent agriculturalists have a declining ability to determine their own future as they have become increasingly dependant, as a production sector, on non-agrarian funding supplied in conjunction with technologies designed or developed by non- farming professionals, whose findings are extended to the farmer in the form of official advise and recommendations, sponsored by agricultural service industries (FIG.32).
The adoption more recently of actor orientated ideas surrounding agricultural research, typified by the farmer first type approach, can be seen as an attempt to escape from certain structural boundaries in attempting to understand farming decision making, and is often associated with the evaluation of more marginalised group needs.
This can be deceptive as it tends to assume that by analysing the situation from an alternative, and apparently less hierarchical, viewpoint that strategies resulting from an approach are intrinsically more correct. This can actually increase the coercive power of structural strategy, as it assumes that methods seen as more representative of the farmers viewpoint, can be superimposed onto the overriding implementation of strategies thought to be better for the farming community, but still emanating from conventional hierarchical theories.
Many such models conceive themselves to be using farmers own knowledge as a base for appropriate strategies, but a true respect for “indigenous technical knowledge” seems hard to assimilate with the use of research work to locate and remove constraints on technical package adoption.
The irony of such an approach tends to emerge when having described the need for actor-orientated approaches and when the value of farmers knowledge has been accepted, the farmers role within research work remains centred around providing a means for encouraging use of new package technologies, and as a source of study of the effects of enterprise adoption.
This use of the farmer as a resource can be seen in the underlying view that actor-orientated approaches can over value indigenous technical knowledge, pointing to the idea that whilst an experienced practical input is useful, it should be kept in its place within the larger theoretical strategic concerns.
CONTROL OVER DECISION MAKING
Attempts at a practical level to address issues of unsustainability within agriculture, have been seen to develop alongside theories of farmer empowerment, but seem unwilling or unable to resist the charms of much grand theory in terms of the broad trajectory of agricultural development, leading to an application of low input research, mainly in resource poor areas, to look at ways of gaining a foothold on the agricultural growth path.
External inputs being seen as more applicable the more “developed” a farming system becomes therefore fail to address sustainability through improved husbandry interacting with the flow of substance and forces within their agro-ecosystem (Chambers 1994).
This seems to reflect the unwillingness outlined above to really empower farmers on a theoretical or practical level, due to the perceived necessity for, or at least acceptance of, larger external influences to have the final say over agricultural production.
Through the use of available knowledge within the farming community it can be seen that agricultural output can be linked more strongly to farming ability, through a reliance on knowledge of natural processes, but the resulting supremacy of the farmer himself in such a system concerns those whose only involvement in agriculture is centred around the academic study of it, either as part of a socio-political appraisal or involved with the scientific development and refinement of input packages and their consequences.
All human activity concerned with management of an ecosystem can be seen to disturb biological cycling within it, but with adequate knowledge of the process at work and their interrelationships, can allow this disturbance to be productive whilst not destroying the natural cycles themselves. Where these processes are made redundant through input substitution productive cycles can be identified as fundamentally different, with artificially controlled inputs to a predetermined growth cycle.
Such techniques show an important break from a reliance on either, farmers own knowledge of agroecosystems and the biological cycling within them, and are typified by the conception of farm land as a shop floor over which various ingredients pass in the making of a product, and therefore replaces traditional farming wisdom with business management skills, and substitutes fertility for soluble nutrient availability
combined with ancillary crop protection technologies with potentially important consequences.
The use of farming systems approach has been linked with the desire of economists and other social scientists to become more involved in setting priorities for technological research as it was felt it could enable them to establish links between experimental projects and farmers themselves (Beets 1992), however farming systems research in its modern form perhaps favours the economists standpoint, due to the increased role of institutional capital in agriculture, and subsequently fails to appreciate the dynamic situation facing the farmer, and that constant attention should be given to all interactions within the managed ecosystem (Maxwell 1986).
Approaches based around problem identification and problem solving in an attempt to isolate constraints on the success or explanations for the failure of specific techniques or farming systems as a whole, these are typified by ecosystem analysis (Borden et al 1985) but can also lend themselves to hierarchical concepts of different farming systems or regions or over emphasise role of capital to control the environment.
The almost chaotic and constant re-shuffling of variables and priorities which allows instinctive decisions is thus the major feature of farmers knowledge, and within a context of such husbandry, outside knowledge is viewed in a variety of ways – involving its perceived applicability, relative costs and benefits and suitability to the intricacies of the farmers well known habitat.
Experimentation with neighbours and the reconstruction of ideas in tune with the farmers own perceptions is therefore all undertaken if it is seen as relevant. This process though, remains at the choosing of the farmer. As trends have been identified showing a flow of adopted procedure in the wake of “optimal models” put forward through structural adjustments made by external influences (as above), there is nothing to suggest that this is through preference for the practises involved, in fact the opposite has been suggested (eg. subsidy hunters).
CONCLUSION
This draws doubt on any conclusions that the temporarily favoured optimal models adoption is backed by faith in it, specifically on the part of the farmer. But suggests that a readjustment of the optimal modal to, for example, one stressing optimum use of on farm resources for nutrient replenishment and therefore less costly output, might result in similar pattern of adoption, and it can be seen that it would significantly effect the independence of the farming community, from interest groups related through market mechanisms to the agricultural industry -through increased market flexibility and lower costs via less substitution of primary solar productivity with damaging forms of imported energy – which have been shown to significantly undermine the farmers position as the manager of a healthy and increasingly productive resource base.