Patterns of input–output relations in agro-ecosystems
Dirk Zoebl
∗Midden-eng 29, 6721 GV Bennekom, The Netherlands
Received 7 March 1997; received in revised form 8 September 1999; accepted 23 December 1999
Abstract
Two different patterns in input–output relations can be distinguished in agricultural production. For the first, yields are obtained at zero rates of certain external inputs, such as in wheat growing, or dairying based on grazing. For a second type of input–output relation, inputs are required before any yield can be obtained, such as in irrigation schemes in desert areas, or industrial production at large. Inputs for agricultural production, unlike in industry or commerce, generally consist of natural resources such as rain and soil nutrients, and of external inputs involving cash, such as industrial fertilizer or pumped irrigation water. If the share of these natural or internal resources is taken into account, constant marginal returns to input application may occur where, at first sight, decreasing returns (for the first relation) or increasing returns (for the second) appear to apply. These hidden risks of misinterpretation of field data or survey statistics occur, e.g., in crop physiology, dairy management, irrigation and the economy at large. Some implications are sketched for agricultural research and policy in low input husbandry systems, for energy use efficiency, and land use programmes in developed and developing countries. It is argued that, for a wise and responsible resource use policy, a narrow economic view is misdirected; instead, a broader, long-term agro-ecosystems perspective is needed. © 2000 Elsevier Science B.V. All rights reserved.
Keywords:Production functions; Input use efficiency; Virtual value; Increasing versus decreasing returns; Industrial versus natural resources
1. Introduction
Agriculture, so it seems, can no longer be left to farmers, agribusiness and agricultural science only. In the definition of agro-ecosystems and sustainable land use by Conway (1985), socio-economics are as es-sential as the agrotechnical and biophysical aspects. It soon became clear, however, that communication among agronomists, ecologists and social scientists is rather problematic (Tisdell, 1988). Small wonder that, where scholars attempt to catch the concept or essence of sustainable land use, their respective backgrounds can often easily be traced. As a result, the development of a suitable set of criteria or indicators to
operational-∗Tel.:+31-0318-418685; fax:+31-30-2318127.
ize this new social challenge may turn out to be as elusive as Lewis Carroll’s ‘The Hunting of the Snark’. Generally, in scientific literature a standardized and systematic way of presenting methods, results and conclusions is used. Well defined parameters, quantifi-cation, adequate field trials or surveys, causal or sta-tistical analyses or other unambiguous criteria are the means. This methodology and arsenal, so successful in the natural sciences and applied biological disci-plines, is common also in agro-ecology. For example, Conway (1985) defines agro-ecological sustainability as the ability to maintain productivity in the face of in-tensive stress or shock. Soil scientists familiar with the slow and mostly imperceptible decrease of soil qual-ity under certain husbandry practices, however, may have problems with this definition, more so than pest control specialists like Conway. On the other hand,
farmers, when pondering sustainability, might be more concerned with their bank debts or access to subsidies and compensation payments. Recently, sustainability (Hansen and Jones, 1996; Viglizzo and Roberto, 1998) and stability (Viglizzo and Roberto, 1998) of some American farm systems have even been defined ánd quantified. Such an approach might lead up a blind alley. Why attempt to apply rigorous scientific meth-ods for agro-ecological characteristics, where these depend on variable farm conditions and often also on social wishes or whims?
This study does not attempt to define concepts, to quantify parameters, to work out tools for a compre-hensive approach, or even to provide new findings. Instead, two types of input–output patterns underly-ing complex production functions are presented. A graphical representation of these functions is given and elucidated by practical examples from plant physiol-ogy, dairy management, irrigation and the economy at large. The complexity of land use systems means that, generally, a variable mixture of natural resources and industrial inputs is required. Because of this dual char-acter of inputs, pitfalls exist in quantifying and evalu-ating production functions. Many conflicting views on production functions of the rural scene, however, will be shown to be paradoxical; that is, only seemingly contradictory.
It is hoped that the perspective and the exam-ples presented here will foster the discussion of philosophy on externalities of the narrow economic
Fig. 1. The two types of production function as explained in Section 2. For an explanation of the points Q and R, see Sections 3.4 and 5.1, respectively.
view (Dahlberg, 1986), because society nowadays is asking more from agronomists and land use plan-ners than only economic analyses and technical performance.
2. A graphical representation
The simplest set of production functions introduces some basic relations, terms and a graphical represen-tation in a convenient way (modified after de Wit, 1960). Fig. 1 presents two categories of production functions. For simplicity, the functions are linear and the rates of increase are equal. The difference thus merely consists of the intercepts with the x -andy-axis. In function Type-1, an output is realized without certain apparent or external inputs. Function Type-2 shows an output taking off only if an initial expenditure of certain inputs is made. Mathematically, functions can be expressed as:
• Function-1:y=ax+b, with interceptbon they-axis atx=0;
• Function-2: y=ax−c, with intercept c/a on the
x-axis aty=0.
Examples occurring in agro-ecosystems are as follows:
increasing rate of concentrate feeds (the production without concentrates has valuebatx=0).
Function-2: (I) Crop production with irrigation in a
desert area. (II) Pork and egg output in the bio-industry at an increasing rate of feeds (the maintenance feed being mainly responsible for thec/aintercept).
In this graph, there is no place for diminishing returns to increasing inputs. In scientific trials and agricultural practice, diminishing returns will invari-ably occur as soon as inputs can no longer be applied (or taken up by animals) in balanced rations, or where growth factors such as water or radiation become limiting (Janssen and Guiking, 1990). However, the following examples will be shown to be within the trajectory where balanced or counterbalanced bound-ary conditions reign.
3. Four cases of input use efficiency, and the virtual point Q
The unsophisticated mathematical expressions as given lie at the core of most production functions in agriculture and other ecosystems, whether in the nat-ural or the human realm. Their nature may remain ob-scure, however, because agricultural research results or statistical tables are often presented in a trajectory beyond the intercept values. Such a presentation can be inevitable, because these intercepts are often ob-tained by extrapolation beyond practical reality. More often than not, paradoxical, or even conflicting views are the result, as will be shown.
3.1. Nitrogen use efficiency in leaf canopies
Nitrogen is essential for the photosynthetic assim-ilation of plants. Leaf nitrogen content per unit area, therefore, often reflects the potential for photosyn-thetic leaf assimilation per unit area (Sinclair and Horie, 1989). The ratio between these physiological characteristics is a case of nitrogen use efficiency, an important growth parameter (Lüttge, 1997). Plants and plant parts have long been known to have the plasticity of adapting their photosynthetic potential in a functional way. Givnish (1988) considers that leaf and canopy traits can only be understood in terms of their effect on whole-plant carbon gain, not on leaf level assimilation alone. To use the phraseology of
Field (1988), whose work on N use efficiency inPiper
spp. is extensively cited by Lüttge, the following general mechanism is now ‘conceptually reasonable’. Where growth conditions are expected to be good, single leaves invest heavily in N-content and photo-synthetic capacity at a certain ontogenetic stage. With favourable growth conditions, these investments are paid for. However, where these optimal conditions are not met, assimilation and N use efficiency would have been better with lower N contents in leaf tissue. This low level of nitrogen can be realized by a mod-erate investment during the period of leaf formation (Field, 1988), or by a retranslocation in senescent or shade leaves (Givnish, 1988). Therefore, early crop simulation models such as ELCROS (de Wit et al., 1970) had only limited predictive value, because they were based on rigid single leaf assimilation functions (Zoebl, 1972).
Lüttge (1997) noticed that the curves representing the N use efficiency of single leaves of some Ama-zonian forest species, measured at a set of ecological conditions, often do not appear to extrapolate through the origin, thus showing reduced N use efficiency at the lower N levels. Concurrently, increased efficiency occurs at the higher levels, and this appears to apply especially where intercepts, thus N levels, are high, as in plants grown in habitats with high light intensi-ties or resource acquisition (Lüttge, 1997), or in leaves with persistent photosynthetic activity (Field, 1988, Fig. 2). Such a steering of the photosynthetic capac-ity by way of adaptive N distribution in plants may be seen as a series of a Type-2 pattern of input–output relations, although with variablea- andc-coefficients. The model is subject to the rule that input–output ef-ficiency often depends on the investments in capacity to perform. It should still be noted that the physiolog-ical mechanism as described is not the only strategy for plants or plant parts to maximize their competitive ability or biomass accumulation. Thus, the described pattern is not unique.
3.2. Nitrogen use efficiency in Dutch dairy farms
Fig. 2. Correlation between photosynthetic capacity and nitrogen levels in leaves ofPiper hispidumandPiper auritum. The persistent leaves ofP. hispidumappear to invest more heavily in N-content per unit area than leaves ofP. auritum, shedding its leaves more easily. Original data from Field (1988), with added drawn lines (range in which measurements were obtained) and extended dashed lines (extrapolations) by Lüttge; individual observations are deleted.
respectively (Table 1). de Wit (1992) adapted other, similar figures from van der Meer on the gradual in-tensification of dairying in the Netherlands (Fig. 3), but reached an opposite conclusion. He argued that the efficiency of N use did not decrease over time, in spite of the dramatic increase of N inputs during those years. The paradox may easily be explained by
Table 1
Nitrogen balances (kg N/ha/year) of dairy farms in 1975–1976 in the Netherlands with intensive and extensive management (van der Meer, 1982)
Intensive Extensive
Nitrogen input:
Fertiliser 383 –
Biological fixation – 65
Purchased feeds (5389 kg DM) 127 870 kg DM 24
Precipitation 23 23
Total 533 112
Nitrogen output:
Milk (13511 kg/ha per year) 72 5867 kg/ha/year 31
Liveweight (468 kg/ha per year) 12 250 kg/ha/year 7
Total 84 38
Nitrogen not accounted for 449 74
N-output/input ratioa 84/533=0.16 38/112=0.34
aThe N-output/input ratio is additional.
Fig. 3. Input–output relations of nitrogen in Dutch dairying from 1965 to 1985. The apparent output per unit input seems to de-crease at increasing input rates (when the contribution of soil-N is not deducted), but the marginal responses to external inputs are constant (adapted from van der Meer, in de Wit, 1992).
In low input systems, a larger part of the output arises from N supply from precipitation, biological N fixa-tion, N mineralisation or other natural processes with no monetary expenditures involved. The marginal in-creases remain constant, however, all along the time trajectory. Thus, the large differences quoted by van der Meer between extensive and intensive, or in inten-sifying management systems, are mainly illusory.
A further analysis of the remarkable constancy of the marginal increases focuses on the changing ratio of fertilizer-N/concentrate-N during the time span. In the beginning, total N input contained relatively more fertilizer, at the end more concentrates per ha, partly via a higher dairy/pasture density (van der Meer, 1982). Thus, diminishing returns as occurring in N-fertilizer dressings at increasing rates could have been more or less counterbalanced by the increased gain in efficiency from a greater input in the form of concentrates, because the N use efficiency of balanced feeds is higher than that of the two-step conversion of fertilizer-N to grass to milk.
3.3. Water use efficiency in alfalfa
Another interesting case of input–output relations subject to a variable interpretation of field figures is
an experiment on irrigated alfalfa in Oakes, North Dakota, by Bauder and Bauer (1978). When compar-ing the field water use of this crop at four irrigation rates, Huibers and Stroosnijder (1992) state that it could easily be concluded that the efficiency increases with increasing rates: apparently, less water is needed per kg of forage at the higher rates. However, again, this is only seemingly so. In this case, input–output relation Type-2 applies. Thec/aintercept (Fig. 4) rep-resents mainly non-productive water (soil evaporation, unavailable soil water and other losses to the crop). This amount appears to be constant, irrespective of the treatments (Huibers and Stroosnijder, 1992). Beyond this intercept, the marginal water use efficiency ap-pears to be constant over the trajectory of treatments. As in the section on Dutch dairying, it seems ap-propriate to further analyse and speculate on Huibers’ and Stroosnijder’s interpretation. The linear extrapo-lation and the 100 mm intercept (Fig. 4) may be seen to express the authors’ assumption on the crop wa-ter use efficiency, as is also, and more explicitly, pro-nounced by Richards (1991) in his hypothetical linear water use functions. An S-type response curve, how-ever, is more likely to occur, as is sketched in the alternative dashed lines of Fig. 4. At the lowest use levels, responses increase; at supra-optimal rates, they gradually decrease (Fig. 4). Because of lack of field data in the specific trajectories, this cannot be proved, but it is likely because of inefficient water use through relatively high evaporation losses at the lowest water use levels. However, even if confirmed by field trials (in trajectories without practical relevance), this does not invalidate the simple, linear response curve as pro-posed by Huibers and Stroosnijder. Obviously, these authors had the crop water use component of the pro-duction function in mind, not the overall field response to irrigation and seasonal rain combined.
3.4. The critical point Q: unrealistic but important
Fig. 4. Yield responses of alfalfa to irrigation treatment in N. Dakota. Drawn straight line: response as envisioned by Huibers and Stroosnijder. Dashed curved lines: alternative response as suggested by M. Smith. Water use efficiency appears to increase when the evaporation and other water losses (the intercepts) are not deducted. Marginal responses in both cases are, however, constant in the trajectory of treatments.
value, because no farmer will ever consider applying inputs to a level at which he cannot harvest something, as was already long ago expressed by the husbandry economist Aereboe (1923). Even scientific trials with input levels where outputs would be about zero are uncommon, with the annotation that this applies more to field crops than to livestock, where preservation at maintenance costs might make sense. Under the con-ditions of the above cited alfalfa trial, the water use for zero return appears to be 100 mm per crop season in Huibers’ and Stroosnijder’s linear response function.
Even if virtual, this point Q has practical mean-ing. In analogy with zootechnical calculus for feed conversion (van Es, 1972), it could be maintained that the ‘maintenance’ application consists of the non-productive water because of evaporation, dissipa-tion and unavailable sorpdissipa-tion that may occur before water is taken up and transpired by the crop as part of the production process. In the animal feed analogy, the maintenance feed cannot be simply measured. Some authors even state that a distinction in maintenance
and productive feed is completely artificial (van Es, 1972). Whether for convenience or otherwise, where quantification of this maintenance feed is aimed at, it has to be approximated by extrapolation of the per-formances of animals with varying production levels towards the zero production level (van Es, 1972). As is the case in animal physiology, the portman-teau term evapo-transpiration from crop physiology clearly indicates that evaporation and transpiration cannot easily be separated. Nevertheless, knowledge and best estimates of the virtual amount of water for evaporation and other losses to the crop is important for technical and economical evaluation of irrigation and dry farming systems.
3.5. Decreasing and increasing returns
principle of increasing returns applies as often as that of decreasing returns. In branches of industry where large initial investments have to be made, such as in the airplane and software industry, marginal costs per unit produce may fall dramatically as outputs or mar-ket shares increase. This applies the more so, where so called lock-in processes or pioneer advantages occur (Arthur, 1990), as is also noted by software manufacturer Bill Gates (1995). Consequently, the producer’s margins improve: increasing returns of input–output function-2I apply where costs are cal-culated as combined fixed and variable expenditures (Fig. 5, the accentuated form is chosen for these com-mercial input–output relations where no soils or other such natural resources are involved).
Modern agriculture is increasingly an industrial pro-cess, with a decreasing share of natural resource ex-ploitation; hence, the concept of increasing returns also applies to agriculture. de Wit (1979) found in-creasing returns even in practices carried out by hand labour such as in land amelioration or irrigation. So, also in non-industrial, low-input production systems, increasing returns to labour inputs may apply at in-creasing yield levels, where yield is plotted against the combined efforts of reclamation and seasonal field operations. De Wit’s statement seems to contradict
Fig. 5. Input–output relations at varying shares of fixed inputs. At increasing outputs, increasing returns to combined fixed and vari-able inputs applies. The effect is gradually reduced at decreasing fixed inputs. Where fixed inputs are zero, constant returns to vari-able inputs applies (Function-3). For an explanation of Function-2I
and the one in-between, see Section 3.5.
Arthur’s insight that agriculture is for the most part subject to diminishing returns. The paradox can be re-solved by focusing on the pattern of the single func-tions of the production complex.
Fig. 5 also shows function Type-3, the response curve where fixed costs are zero. In this function, re-turns to variable inputs are constant. An example is the wage of a farmhand with increasing input of work-days. Finally, the figure reveals that gain in output at increasing labour inputs is almost constant where fixed investments are very small or negligible, such as in weeding a crop by hoe by the farmer or his family members.
4. Some tentative conclusions
What can be learned by biologists, ecologists, engi-neers, economists and other scholars of complex pro-duction systems by considering these varying patterns of productivity?
Ever since Frederick (‘expansive’) Taylor launched his concept of technical and economic efficiency in factory work and similar enterprises, the concept has gradually gained such momentum as to have been cited to define our age (Porter, 1997). Not only indus-try and commerce, but also modern agriculture and bio-industry are shaped by the compelling urge for ef-ficiency. However, whereas technical and economical efficiency generally can be well defined and quanti-fied, this is less so for the inevitable trade-offs of such gains in efficiency, as are autonomy and leisure (Porter, 1997). In agro-ecosystems, this efficiency can be at the expense of soil quality, human health, the environ-ment, biodiversity, animal well being and landscape quality. The development of a conceptual framework and methodology to study the agro-ecosystems’ health is still in its infancy. However, some tentative con-clusions can be drawn from the examples presented above:
2. The evaluation of husbandry systems such as dairying or irrigation can evoke conflicting or para-doxical views. Lack of a uniform way of looking at such husbandry systems is the reason. The as-sessments of the decrease or increase in efficiency of a system depends often on the role and weight of internal inputs such as rainwater, soil nutrients and microbial activity. The outputs require external inputs expressed in money terms, and internal ones without a monetary equivalent. This assessment is further complicated because the share of internal inputs may depend on the level of external inputs (e.g., sustained, yearly N fertilization may increase the internal seasonal N availability, see Wolf et al., 1989). A two-pronged or interdisciplinary approach might now be needed, combining the efforts of agricultural scientists and economists. 3. In all the examples given, the efficiency of
input–output relations depends on the initial pres-ence of, or investment in, certain inputs or growth conditions. The overall input use efficiency de-pends on the combined variable inputs and natural resources or fixed investments. Again, these com-bined inputs cannot always be distinguished well, or expressed in a single equivalent, which may account for misunderstandings between scientists and economists. Decreasing apparent returns to in-creasing external inputs may occur where a certain output level is obtained without any initial external inputs, even where the marginal efficiency at in-creasing levels of these variable inputs is constant. 4. For biophysical, technical or economic systems, al-location choices may exist before the beginning of the production process. How much to invest in a special input or combination of inputs for future production capacity? A high capacity is only re-alised with favourable production conditions, but it often means reduced productivity where these con-ditions happen to be unfavourable.
5. In industry and agriculture, the initial investments in capital or efforts cannot be changed at the be-ginning of the production process: the production capacity is now largely determined. At low invest-ment levels, more or less constant input–output re-turns are obtained. At high investments, increasing returns may apply, even where the marginal pro-ductivity arising from the variable inputs remains constant (Fig. 5).
5. Implications for agricultural research and land use policy
To show the relevance of the presented perspectives for land use planning and research policy, some topics of interest are outlined, without any pretence to be exhaustive.
5.1. Exploitation or conservation of natural resources
Without any labour or capital, no rural production or resource exploitation is possible, although the capital inputs come close to zero in shifting cultivation. De-pending on the mix of labour and capital incurred, an output R (Fig. 1) from a certain land area is obtained by production function Type-1, without any fertilizer or other inputs involving cash expenditures. This pro-duction situation can be obtained with either much labour and little capital or the reverse (de Wit, 1979; Giampietro, 1997). Good examples of capital exten-sive systems are shifting cultivation and backyard live-stock systems. Examples of labour extensive systems are ranching in the USA and Australia.
Whatever the mix of capital and labour, the biophys-ical contributors to farm income (rain or other ‘free’ water, soil nutrients, microbial and other soil life, natural grass and other flora) are often hidden from economists because they cannot easily be expressed in monetary equivalents. Many of the paradoxes around efficiency of external inputs in agro-ecosystems can be attributed to a lack of awareness of the varying contributions of natural resources to agricultural out-puts, as shown in the Section 3.2. van der Pol (1992), describing a production function of Type-1 of small scale cotton farming in Mali, gave his paper the com-pelling title: ‘Soil mining, an unseen contribution to farm income in Southern Mali’. Unseen indeed gen-erally, by economists and most agronomists, but not by the more experienced agronomist, farming system economist, and, probably, the farmers themselves. For, by choosing to break new lands when yields start to decline, a rational short-term option is pursued. The mining of soil nutrients in sparsely populated areas such as the Sahel is cheaper than the purchase of fertilizer, or the restoration of soil fertility with organic means.
husbandry day in Wageningen in 1992. It appeared to broaden the views of the agricultural audience, even of the soil scientists among them (B.H. Janssen, personal communication). His thesis, however, was the re-appraisal of very old husbandry knowledge. Mayumi (1991) cited Liebig’s indignation at the alarming yield decreases through exploitative hay cropping in Massachusetts during the 1840s. Aere-boe (1923), however, appeared to side with the Mali farmers by stating that soil conservation is uneco-nomical in areas with abundant soils, by exhausting farm labour and capital.
In historical and contemporary situations, soil con-servation makes sense only where soils become scarce because of population density or other socio-economic reasons. In the past, the transformation of resource exploitation to a conservational way of farming gen-erally took place in a gradual way (Hayami and Ruttan, 1985). Calamities from inappropriate hus-bandry, though, have occurred, as is known from the dustbowls of Oklahoma and Kazachstan. One may seriously doubt, however, whether the general trend of a change to conservational farming will also apply to the developing nations of today. The sharp increase in population, the higher aspiration levels and other socio-economic factors seem to favour short-term resource exploitation at the expense of resource con-servation (Mayumi, 1991; Ehrlich and Ehrlich, 1996). Without considering the hidden aspects of soil or other natural resources, land use policies are short-sighted, and, therefore, are bound to fail (see also Zoebl, 1997).
In modern irrigation, another type of hidden draw-back may play a part. Is it possible to avoid invest-ments and inputs, required to obtain a certain yield? Often, it is now the technician, engineer or agronomist who are myopic. For example, before expensive ir-rigation systems are adopted, it should be ensured that rainfed agriculture cannot profitably be improved (Pimentel et al., 1973; Carruthers and Clark, 1981). Engineers enjoy the challenge of designing irrigation schemes, breeders come out with miracle crops; both are examples of high-input/high-output systems of pat-tern Function-2. Especially in developing nations, bud-gets for such developments and systems are small. Thus, the alternatives of producing with much lower investments in external inputs have to be considered, as shown further.
5.2. Low input agriculture: potentials and limits
The output R (Fig. 1) obtained by farmers without any industrial inputs is wrested from the allocation of some land and family labour. Incomes thus obtained in produce or monetary equivalents are generally poor at Western standards.
That is a main disadvantage. There are, however, also advantages for the peasants, herdmen and min-istries of developing nations concerned. Farm com-munities in these production situations are mainly self sufficient and ministries can save on their budgets for national food supply and agriculture. Where the needs for food and other basic needs are ensured, and some modest surpluses are sold on regional markets, all or part of the national needs for food and fibre are cov-ered with only moderate strains on the budgets of the relevant ministries. In fact, this simple procedure has made it possible for the advanced nations of today to do without public agricultural research, education, extension and other such services until rather recent times, say a century or so.
A case in point is China’s hog industry. At present, most Chinese pigs are backyard animals, fed mainly with water plants, vegetables, tubers and scraps from household meals (Tuan, 1993). In short, a production function Type-1. In the 1980s, only 10% of total na-tional grain output was fed to all livestock, a quar-ter of this amount in the form of mixed or balanced industrial feed (Tuan, 1993). Is this industry now to move in the direction of capital intensive husbandry systems with uniform, industrial feeds based on grain and oil seeds, as is advocated by Tuan (1993) and Pin-gali (1997)? Or is this jump premature, and should government policy aim at small scale, labour intensive traditional units, cautiously adapted to cope with the modern situation of a growing market for red meat? Or is a dual approach the best, combining some modern industrial units around the larger cities, with the sup-ply of the giant mainland left to backyard producers and local markets? This latter approach requires gov-ernment efforts in animal health care services, supply of suitable breeding boars, adapted research in breed-ing, finisher meals matching backyard conditions and other such technical and organisational measures as advocated by Udo (1997).
devel-opment specialists too often have their eyes fixed on the mature development stages, at the expense of the early, resource based and labour intensive husbandry systems. Whatever China’s future, the political choices made now will influence rural employment, foreign exchange needs, national budgets for infrastructural works, type of research and extension, environmental and landscape quality, and maybe even world trade and price levels of grains and oil seeds.
The Chinese pork’s tale is only an example. Similar cases can be given for fish (e.g., Gomiero et al., 1997), poultry, milk, medicines and transport, among others.
5.3. Energy use efficiency
Pimentel et al. (1973) were first to provide a com-prehensive, quantified picture of the demands for fos-sil fuel in modern agriculture and agribusiness. Later, Pimentel and Pimentel (1979) estimated decreases in fossil fuel inputs by two-third, were USA farmers to extensify by reducing from the then common yield levels of 5000 kgs down to 2500 kgs corn per ha. This and other estimates may warrant alertness and raise ar-guments to extensify production. de Wit (1977), how-ever, concluded the opposite and predicted increasing energy efficiency at increasing yield levels, with the extra advantages of a reduction in environmental load-ing per unit output and more land available for na-ture and recreation. His prediction came true in farm management studies by Bonny (1993), who carefully analysed modern wheat farms in France and calcu-lated fossil fuel energy needs of 2.65 GJ per tonne of wheat at the high yield level of 8.5 t ha−1 as against 3.85 GJ at a yield of 4.5 t ha−1, obtained at lower lev-els of external inputs. However, as stated by de Wit (1979, 1992) and Uhlin (1999), the superior efficiency of these high yields only holds where expensive recla-mation measures have been taken and a capital inten-sive way of farming has matured. Breman and de Wit (1983) also showed that livestock production systems measured in kg protein per ha per year in Sahelian no-madic systems is as high as, or sometimes even higher than, ranching systems with similar rainfall conditions in the USA and Australia, and in the former with-out any fossil fuel use. Gross labour productivities in those former systems, however, are between 1/15th down to less than 1/100th of those of modern ranch-ing systems. Also, Breman and de Wit (1983) stress
that the practice of keeping large herds with a low production capacity per head is the best strategy in the Sahel, because of the prevailing variable quality of natural grazing. They argue that not water, but nitro-gen is normally the limiting production factor in the Sahel, and that nitrogen use efficiency is maximized by these nomadic husbandry systems, mainly because of the reduction of nitrogen losses by volatization and fire. Their analyses appear to support conclusions 1,4 and 5 of Section 4. What is valid for Sahelian nomadic systems, appears to apply also to the Mali cotton farm-ers of Section 5.1. These farmfarm-ers try to maximize their incomes, not by resorting to fuel intensive industrial inputs, but by maximizing the area cultivated, at the expense of yield levels (van der Pol, 1992).
Stanhill (1981), in line with the philosophy on irri-gation efficiency by de Wit (1992), noted an increase in Israel’s irrigation efficiency per unit water applied over the period 1956–1976. Higher yields and better irrigation techniques, i.e. an increased proportion of water productively transpired by the crops, were seen as the main reason. Stanhill also emphasized, how-ever, the ‘more than commensurate increase in fossil fuel input’, when comparing the modern irrigation methods with less sophisticated techniques. Stanhill stressed that, in the end, the choice between irrigation techniques all boils down to the economic efficiency, determined by the prices for irrigation-water, produce and labour. However, this economic efficiency, so important for the individual farmer, is quite differ-ent from the agro-ecological efficiency as dealt with in this study, which appears to be mainly a social criterium.
providing a sound basis for a productive and benign land use stewardship.
Acknowledgements
The author’s main acknowledgement goes to the late professor C.T. de Wit, formerly head of the Department of Production Ecology, Wageningen Uni-versity. Hein ten Berge, of the same department, is thanked for his corrective remarks on early versions of the paper. Martin Smith, technical irrigation officer at FAO headquarters, Rome, suggested the alternatives in the graph of irrigated alfalfa. The comments and suggestions of an anonymous referee are also grate-fully acknowledged. The Editor-in-Chief caregrate-fully edited the manuscript, provided many useful com-ments and is especially thanked for suggesting the term ‘agro-ecosystems health’. Ed and Pam Verheij are thanked for correcting the English and improving the style. Furthermore, U. Lüttge, H.G. van der Meer, F.P. Huibers and L. Stroosnijder are thanked for their permissions to make use of tables or graphs from their research. Fadma El Kandoussi meticulously worked out and computerized the manuscript.
This study was carried out independently, with pri-vate means.
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