GM plants as sources of im/possibility: a developmental systems view of stabilization

Abstract

This paper generates a heuristic understanding of the stabilization dynamic of genetically modified plants. This heuristic, the paper argues, can provide a fruitful platform for studying the political dimensions embedded in GM plants. Focusing on stabilization is important, because outside laboratories a plant can have an intermediating role only as a cultivar; as something which has integrated into biological processes and human practices. The actual stabilizing entity is not just an object, but a dynamic analogous to what is called a developmental system. The empowering or suppressing consequences of GM plants depend significantly on the qualities of this spatio-temporal order stabilizing; on the “possibility space” it opens up. Moreover, stabilization connects and makes things possible, but it does not do so automatically, predictably – or for everyone. Centralized control may support stability, but it may also increase vulnerability by reducing local possibility space.

Keywords:

• GM plants
• stabilization
• developmental systems
• possibility space

1. Introduction

Genetic modification radically increases our capacity to breed plants and to restructure the production of food, fabric – and perhaps even that of timber. No wonder, then, that green biotechnology is viewed as one of the tools potentially useful in the fight against malnutrition and rural poverty. However, the opponents of the technology note that it is not self-evident that the potential benefits will outweigh the equally likely risks. Moreover, the critics continue, the changes in the orders of primary production accumulate power and profits for the biotechnology companies rather than to those in need.

On the other hand, it is clear that few social or societal implications follow directly from a particular type of breeding technology. For one thing, the varieties and their traits differ significantly. Therefore the EU regulation on the so-called deliberate releases, aiming at preventing environment and health risks, stipulates that assessments of GM crops should be done by focusing on one variety at a time (Directive 2001/18/EC).

However, it is doubtful whether even a variety-specific analysis can reveal what is significant in an innovation of cultivation technology. This is because outside laboratories a plant has an intermediary and political role as a cultivar; as something which has integrated into biological processes and human practices. In order to survive and to produce crops as expected, a plant must stabilize to a complex set of processes and interactions.

Stabilization may result in unpredictable reorganization of relations and associations, but, if the technology is to work, the reorganization cannot be arbitrary: it must fulfill specific criteria. The plants are sources of scripts, which “define a framework of action together with the actors and the space in which they are supposed to act” (Akrich 2000 [1994], p. 208). By imposing demands for their context, the organisms, as components of cultivation technology, impose conditions for action and the development of agency.

In this paper my aim is to generate a heuristic understanding of the stabilization dynamic of GM plants, and to analyze the logic by which these objects participate in defining conditions of im/possibility (on such a perspective see Law (2002)). I am particularly interested in the plants as potentially important foundations of rural subsistence.

The concept of a developmental system (e.g. Oyama 2000, Oyama et al. 2001) provides an analogue model for the building of a heuristic understanding. According to Oyama (2000, p. 1) a developmental system is “a heterogeneous and causally complex mix of interacting entities and influences that produce the life-cycle of an organism”. I suggest that an innovation of cultivation technology, and the context of intended use make demands on each other following a dynamic which is similar to the logic by which an organism and its environment stabilize into a developmental system. In both cases, the stabilizing entity is a spatio-temporal order.

In a stable system, what is fascinating is the way the sub-processes and fluctuations interact across scales. Consider, for example, how the flowering of insect pollinated plants interlocks with the seasonal and spatial variation of the fauna able to do the pollination. Such mutual synchronization or entrainment (Deacon 2003, Dyke 2006) of sub-processes creates an order, and makes a set of separate resources a developmental system.

Understanding stabilization as entrainment opens up important perspectives for studying the plants as sources of opportunities and constraints. The heuristic emphasizes the interrelatedness of scripts, pointing to the significance of temporal and spatial synchronization of actions and processes. Ultimately, the potentially stabilizing entity is not just an object but a multi-scalar dynamic. Moreover, what is important, this dynamic cannot change arbitrarily, but only within the limits of its inner order. Possibility space (Haila and Dyke 2006) illustrates the “freedom of action” of the system, stating within what limits it can change without breaking down.

The paper falls into seven sections. In the next one, I introduce the developmental systems view. After that, in Section 3, I extend the perspective from the level of particular habitats to that of technological systems. Section 4 elaborates the emergence, and role, of possibility space in entrained systems. Section 5 sets the focus on edges; on the borderlines between different orders and disorders. Finally, before drawing conclusions, the paper discusses the practical and political implications of the heuristic introduced.

2. Stabilization as entrainment of a developmental system

In some ways the stabilization of a GM plant is a pretty straightforward exercise. After a plant genome has been modified e.g. by means of an agro-bacterium mediated gene transfer, the individual cells containing the transformed genes are isolated from cell cultures and submitted to testing. The experimentations grow in scale, proceeding from laboratories to greenhouses and further to field trials. At each point unstable genotypes are screened out and the lineages appearing stable are chosen for further improvement and testing. Hence testing of stability follows roughly the same “step-by-step” principle which, in the EU, guides the risk assessment of GM plants: “the containment of GMOs is reduced and the scale of release increased gradually, step by step, but only if evaluation of the earlier steps in terms of protection of human health and the environment indicates that the next step can be taken” (2001/18/EC, preamble 24).

The breeders of GM varieties and the regulators of GM releases thus locate the preconditions of stability first and foremost inside the plants. The metaphor of “unfolding” very much persists: the development of an individual is about unfolding and fulfilling a genetic program (Lewontin 2000). This is the case although the recent focus on systems biology emphasizes the importance of systemic interactions and multiplicity of relevant variables (Fujimura 2005). So even in the current post-genomic era, during which the focus has extended from genes to the entire genome, mechanistic analogies and cybernetic underpinnings have remained powerful (Fujimura 2005, Huang 2000). The driving rationale is to identify and to study entities with a distinct regulating function (see e.g. Andersson et al. 2003, Ganeteg et al. 2004).

The atomistic heuristic has been criticized e.g. by Lewontin (2000), who proposes a shift from “command and control” oriented thinking to what he calls a constructivist approach. Lewontin underlines the two-way and multi-scalar nature of biological interactions. Genes affect metabolic flows in cells, but at the same time cell constituents influence the rate and timing of gene transcription and translation. However, it is not only the immediate cellular environment which makes a difference. Predictable development and growth expects compatibility between processes that take place on several scales. Thus, in a laboratory or a greenhouse, the control of the growing conditions demands care. Variations between light and darkness, for instance, must match with the metabolic processes within the plants. A test field, again, is a much more variable environment than a greenhouse. For instance, light is not just “on” or “off”: cloudy and sunny spells fluctuate in asymmetrical and contingent intervals. The variations may cause stress to the plants, and affect the activity of specific genes. Indeed, plants may display very different qualities in a greenhouse from those that they display in a field (Pasonen et al. 2004).

To take the constructivist view seriously means that environment cannot be treated as an independent and purely exogenous force. Environmental conditions greatly affect how an organism develops and grows, but this relationship, too, is bidirectional. During its growth a plant shapes the way it is related to the environment and affects the qualities of its immediate surroundings. For example, utilization of nutrients by cultivars tends to exhaust the soil if no biomass or fertilizers are returned to the resource. However, the effects are not always mere by-products of growth. Instead it can be stated that plants engineer and choose, to a varying extent, their own environment (Laland et al. 2001, Sterelny 2001). For instance, different plant species have different metabolic characteristics and therefore their influence on soil fauna differs, too. Even the choice of plant variety, such as a maize cultivar, can affect the genetic diversity of root-associated bacteria (Dalmastri et al. 1999). The changes in immediate environment can further affect how the plant grows – and how it determines its environment (Lewontin 2000, pp. 56–57). Therefore plant breeders cannot, and actually do not, totally bypass genome–environment interaction. If they are to succeed in their business, they must ensure that the varieties they generate are as insensitive as possible to environmental variations, i.e. that the plants will produce crop reliably and have the expected qualities even if the conditions change somewhat from one time or place to another (Lewontin 2000, p. 26).

The two-way nature of developmental interactions does not imply that stabilization of an organism is a contingent, non-deterministic process. There is causality, but it is circular in nature: what is new and the conditions making the new possible originate at the same time (Haila and Dyke 2006, Peltonen 2006). From this it follows that stability does not reduce to individual variables: it is a result of systemic interaction.

This systemic interaction, bringing together the resources necessary for ontogeny, growth and reproduction, is what makes a developmental system (e.g. Oyama 2000, Oyama et al. 2001). The point is that only when we are ready to drop the dominating dualism between the genes and the environment can we fully make sense of functional collectives that produce stability within and over generations (Oyama 2000, 2001, 2006).

A developmental system is a typical “black box”, an entity “where many elements act as one” (Latour 1987, p. 131), but which has become so established that its content is practically invisible (Oyama 2000, p. 8). This is the case when stabilization is successful. However, when a harvest is lost or the crop lacks the qualities expected, the system, or at least part of it, becomes visible.

The developmental systems view extends the definition of inheritance. Heredity is about reproduction of all those resources that contribute to repeating life cycles: “the precise characteristics of these [developmental] events and their outcomes are a matter of the particular entities and conditions in place, rather than of pre-existing necessities of internal ‘natures’, representations, instructions or codes …” (Oyama 2000, pp. 3–4). Particularly in the case of cultivars, such conditions are partly cultural. Humans need to ensure, for example, that soil remains a resource supporting reliable production of crop.

However, the stabilization of a developmental system is more than a matter of assembling resources. Favorable interconnections between various sub-processes are necessary, too. Processes from molecular to ecosystem level and even beyond must create a functional whole, a multi-scalar order.

Comparability between processes taking place on various scales can be achieved only if the rhythms of relevant physical, biological – and social – cycles synchronize. This implies not that sequences of the cycles are identical, but that they match. For example, Haila and Dyke (2006, p. 33) note that the “turn over” time of cell ribosomes is shorter than the reproductive cycle of a whole cell. However, in a functional cell the slower and faster processes interlock so that the processes can react to each other. Thus a cell – just like, on a larger scale, a flourishing field – is a manifestation of entrainment (Deacon 2003, Dyke 2006).

Entrainment of interactions is a “weakly predictable, order-generating process” (Deacon 2003, p. 274). It produces a pattern, an internal coherence that embodies the rules of its transformation. Some of the sub-processes entrained may have a controlling function over others, but it may be difficult to distinguish causal principles tying the constituents together or controlling the development of the whole. Instead control is “multiple and mobile, distributed and systemic” (Oyama 2000, p. 5).

3. From developmental systems to viable technology?

During the period 1996–2005, the global area of GM crops cultivated increased from 1.7 million hectares to almost 90 million hectares (James 2005). The adoption rates have thus been, according to James (2003, p. 303), the “highest for any new technology by agricultural industry standards”.

The adoption rates, while informative as general indicators, tell nothing about the variety and outcome of particular stabilization attempts. On the other hand, more specific analyses are relatively rare. Among these it is possible to find, however, a set of case studies focusing on the stabilization of GM cotton in South Africa.

In their article “Can GM-technologies help the poor?”, Thirtle et al. (2003) analyze the adoption of insect-resistant cotton in Makhathani Flats, KwaZuluNatal. The region is an agriculture-dominated area with a typical farm size between 1 and 3 ha. Cotton is by far the region's most popular cultivar. However, its cultivation is seriously complicated by insect pests such as bollworms.

In 1998, a GM cotton variety containing genes that control the production of insecticides, thereby making the plants resistant to bollworms, was introduced in the region. The cotton-growers were relatively eager to adopt the crop. A local company provided the farmers with support services, credit for land preparation, chemicals and the GM seeds. Stabilization of the cultivation technology proceeded smoothly. Moreover, the first analyses indicated that the technology had increased productivity and decreased pesticide use:

The results of this survey of 100 smallholders in the Makhathini Flats region of KwaZuluNatal give considerable cause for cautious optimism regarding the impacts of Bt [containing genes controlling production of Bacillus thuringiensis] cotton. (Thirtle et al. 2003, p. 730)

However, a few years later, Gouse et al. (2005) present the same case as a warning example of what they call “institutional failure”. They point out that adoption of GM cotton was, in the first place, possible only by means of the loans provided against harvests. According to the authors, in Africa it is common that loans are paid by selling the crop to the lender. Therefore, when a new, cotton-purchasing firm entered the local market, disruption followed. Some of the growers of Bt Cotton sold their crops to the newcomer and avoided repaying their loans to the old firm. The latter was then practically forced to cease offering inputs on credit. This eventually led to the fall of independent cotton production.

In commercial agriculture, entrainment must naturally cover the whole food chain, consumption included. Another case study, an account by Harvey et al. (2002) about the “rise and fall” of the GM tomato in the UK and in the US points to the challenges of extensive multi-scalar stabilization.

As a potential commodity, the GM tomato first aroused interest in the UK. Genetic modification made the tomatoes better suited for processing, and this promise caught the attention of British biotechnology and food processing companies. As a cultivar, however, the first generation GM tomato stabilized in the USA. There it was much easier to get approval for commercial production than it would have been in the EU.

In the USA, the innovation appeared attractive, too, but for totally different reasons from those that pertained in the UK. What appeared as a useful new quality from the perspective of the US firms was the option to control the ripening of the tomatoes. In the US, the standard practice is to harvest the fruit while still green. Because the GM tomatoes maintained their robustness longer, delayed ripening provided flexibility for the handling and distribution of the fruit.

As a result, in the UK, the cans of purée made of US-grown GM tomatoes found their way on to supermarket shelves, while fresh GM tomatoes entered the US markets. However, neither market conquest managed to introduce a system that was there to stay. In the USA the biotechnology company utilizing the benefits of delayed ripening failed, despite the technological advantage, to effectively integrate the whole production chain. It also became evident that the new variety provided few extra benefits to consumers. In the UK, meanwhile, supermarket retailers faced heavy public criticism, and one by one withdrew GM tomatoes from their product ranges. The timing of the BSE crises supported the anti-GM lobby in their attempt to undermine the system introduced (Harvey et al. 2002, p. 148), although this does not solely explain their success (Jasanoff 2005, pp. 121–123).

What these case studies on GM cotton and tomatoes reveal is that if, in a field trial, a plant is to entrain with numerous fluctuations and interactions, in the “real world” the picture becomes significantly more complex. Therefore it is fair to say that stabilization of a new cultivar to pre-existing practices and orders of agriculture is an achievement, not something we could expect to occur automatically.

The discrepancy between “technological” and “institutional” success points to the non-linear nature of stabilization. This means that greenhouses, field trials and functional production chains, for example, may, at the same time, be closely interlinked by a specific plant variety, and radically disconnected because the systems on different scales all follow their own specific dynamic (Haila and Dyke 2006). By emphasizing non-linearity, the developmental systems view diverges from the reductionist accounts of systems theory (Oyama 2006). We live in a reality of discontinuities and overlaps rather than distinguishable, smoothly ordered hierarchies.

4. GM cultivars and reshaping of human possibility space

In systems of primary production, the ways of working and living together, as collectives composed of both humans and non-humans, may go back decades, centuries or even millennia. Everyday routines, alternations between work and leisure, and the divisions of ownership and possession, for example, follow established traditions and institutions. However, transactions across localities take place, too, and thereby the dynamics of farming communities tend to be more or less translocal, determined by translocal pulls and pushes. The processing industry expects that the products are grown in due process and delivered in the time agreed. In a similar vein, loans must be paid for and perhaps subsidies applied for. Entrainment over scales thus requires, at least to some degree, standardization of the processes that are to operate in synchrony.

In order to fit the standard, individual farmers adopting a new cultivation technology are obliged to stabilize production in a specific way. Realization of economic returns may have a similar effect. For example, forestry based on GM trees requires the use of vegetative propagation and transition to cloning forestry. Such forestry pays off only if practiced in large units allowing intensive management. Viability and profitability thus assume specific practice, and this practice further shapes the material basis of primary production.

The demands imposed by GM plants as biological, commercial and regulatory entities, represent the scripts (Akrich 2000 [1994]) embedded in the cultivation technology. The constraining or empowering role of the technology actualizes through scripts. They bound actors, stipulating within what limits actions can be taken if entrainment is to be supported.

The interrelatedness of scripts and entrainment implies that the room for maneuver available for individual actors is dependent on the operational logic that makes a set of processes a functional whole. This operational logic – the order entrained – defines the possibility space (Haila and Dyke 2006) of an entire developmental system. The concept points out that if entrainment is to be maintained, systems cannot change arbitrarily. Moreover, since spatio-temporal orders follow distinct dynamics, they vary regarding to the limits they set for action.

The notion of possibility space is useful if we take seriously the fact that stability is essentially a dynamic phenomenon. Although the processes of growth and reproduction are cyclic in nature, what actually happens during the repeating cycles is transient: things seldom recur just as they did in the last growing period or 10 years ago. In order to remain vital, the systems must adapt and learn. Possibility space describes the limits in which co-evolution between GM plants and their human and non-human associates can take place. From the human perspective the question is not only about the ways in which farmers, for example, are to organize their lives into phases and rotations from day to day or year to year, but about the ways the system limits what can be done in the first place, and which developmental paths or modes of action appear feasible.

The extension of possibility space manifests itself as increased options. It is possible to achieve the goals of reliable growth and production by following alternative paths. The relationships between system components are flexible. For example, on a farm, rotation can be arranged in various ways, and it is possible to support productivity by farm-specific innovations. What is crucial is that the synchrony between physical fluctuations, biological processes and human practices survives.

For farmers, replacement of a non-GM variety with a GM variety may not appear a radical step to take. Nor does the shift necessarily have much effect on the shaping of possibility space. On the other hand, GM plants explicitly aim at influencing the dynamic of primary production. The new varieties are to liberate producers and processors from a range of material dependencies and restrictions. GM cultivars are often expected to accelerate or intensify production cycles. Breeding based on genetic modification can also improve the quality of the crop, or make the plant resistant to pathogens, herbivores, or to herbicides.

In the Makhathini Flats region in South Africa, during the first two years of its cultivation, Bt cotton produced more crop with less labor than the non-GM varieties. GM plants thus expanded the possibility space by “creating” time. The growths in productivity and reductions in chemical application costs outweighed the higher seed costs (Thirtle et al. 2003). The absence of herbicide spraying also increased the safety of production and the flexibility of farming practices. At the same time, the substitution of one cultivar with another opened up a new techno-social trajectory for cotton production. The benefits of bollworm resistance made the region interesting from the perspective of global cotton markets. The supranational mode of action, however, violated the preconditions of local stability.

5. Edges: in-between possibilities and impossibilities

Since stabilization joins processes taking place on different scales, its success depends on the evaluator's perspective. What needs always to be asked is: what are the temporal and spatial scales that should entrain in order that we can say that the technology works?

It is even possible that a network that for some represents a stable system, is for others rather “a source of chaos and trouble” (Star 1991, p. 42). An NGO report from Paraguay (Semino et al. 2006) claims that fumigations of herbicide-resistant soy fields have caused suffering in communities living next to the plantations. According to the report, the neighbors of the soy fields have lost their non-GM crops. Humans, children included, have been seriously injured, too.

In the Paraguay case processes coexisting in time and place met in unexpected ways, but without favorable synchronization. Moreover, the agents and forces intersecting were not equal. In the example, the GM soy fields represent what Star (1991) calls standard technology: they are the ones affecting the boundary conditions of the others.

People may be forced in many ways to coexist with developmental systems based on GM production. A cultivation technology may affect prices, the common environment and the definition of sound agricultural practice, for instance. Exteriority from standard practice, but association with the same developmental system, may imply marginality, since one is forced to act on the conditions of the system dynamic without being able to contribute to the reproduction and transformation of that order. On the other hand, as a source of distinction, GM production may also support the visibility of the margins (Marsden 2008). Organic farming, for example, may benefit from its status as an alternative mode of production.

The open nature of developmental systems also enables the extension of entrainment. In Makhathini Flats, materialized opportunities created new ones. In a similar vain, following of specific scripts may reorganize relationships so that processes assumed to be unrelated may suddenly be able to interact, even to interlock. What may result is a process of self-organization (Deacon 2003, Dyke 2006).

William Boyd (2003) provides an example from a large-scale self-organization – although he does not use this terminology. Boyd argues that gene technology has speeded up the cycles of plant breeding so that it has become easier to synchronize them with the operational logic of business economies and their product cycles. At the same time the patent legislation and other forms of public control have developed to support the commercialization of plant breeding based on gene technology. Finally, the biotechnology companies have managed to buy seed companies through which they have been able to introduce their innovations to the markets. The interlocking of all these trends and processes has, according to Boyle, created a “new industrial order” in the agribusiness sector in the USA. This development has also affected local soy producers, decreasing their possibility space (Mascarenhas and Busch 2006).

The increasing possibilities of coupling and synchronization may increase the “fluidity” of the technology, making it apt to adopt to very differing circumstances. However, self-organization may also lead to technology failure. It is, for instance, possible that the pathogen resistance of modified plants supports the evolution of the pathogens if precautionary measures are not taken (Gould 1998, Bourguet et al. 2005). Thus the role of humans is also to explicitly restrict entrainment.

In the EU self-organization of GMO releases is bounded limited by considerations of biosafety. The coexistence regulation aims to stabilize an order which isolates GM production from other developmental systems. The conditions set for deliberate releases of GM plants are to safeguard that neither they nor their genes will spread into the environment. Invasion, cross-breeding and gene-flow are viewed as potential threats to biodiversity. Isolation is also done for the sake of the consumers, who have the right to know whether end products on shop shelves are genetically modified or not.

Spontaneous development and dispersal are also restricted by means that control the reproduction of GM crops. As commercial goods, the organisms are not to stabilize without due compensation for those holding patents for the particular varieties. In the USA and increasingly also in the developing countries (World Bank 2006) producers of annual GM crops must purchase new seeds every year from the companies holding the patent for the particular varieties. When this is the case, GM farming cannot be based on seed saving, a tradition still strong throughout the world, and particularly in the developing countries (e.g. Hareau et al. 2006, Mascarenhas and Busch 2006). A potential restriction on seed saving affects, directly and indirectly, the possibility space of farmers. Seed saving makes seed purchases unnecessary, and even partial use of farm seeds serves to keep seed prices from rising. The practice also offers an opportunity for replanting in cases in which the initial sowing has for some reason failed (Mascarenhas and Busch 2006). Finally, in systems based on seed saving, seeds can be seen as a testimony to the local skills and knowledge of the farmers who have chosen the material on the basis of what they have learned from living together with the plants in the specific circumstances of the farm (Borowiak 2004, Mascarenhas and Busch 2006). When seeds become a strictly controlled commodity, this local leaning potential is lost.

6. Discussion: im/possibilities and developmental systems

To claim that stabilization of GM plants is an emergent process changes the way the plants appear to us. As cultivars GM plants are outcomes and demanders of synchronization. By using the developmental system as an analogue model I have emphasized that the stabilization of cultivation technology requires entrainment, the emergence of a dynamic order. Impacts and consequences do not directly follow from the new qualities of a GM variety, or from the technique used in breeding, but materialize because many processes or events synchronize – or fail to synchronize – in a specific way.

GM plants participate in defining what is possible and what is not through two types of scripts. First, by expecting a developmental system, an organism (GM or non-GM) proposes a more or less restrictive form of organization. Second, cultivars are embedded with scripts that impose conditions not only for their survival, but also for their legitimate and profitable production.

In a collective of humans and non-humans, a GM variety is bound to affect the development of possibility space in contradictory ways. Along with new opportunities new restrictions are likely to emerge. Entrainment must be supported, nurtured and kept within boundaries. In the end, what needs to be resolved is what and whose opportunities are the ones that count most.

Tim Ingold (2000) illustrates the divergence of agency in techno-social systems by making a distinction between subject-central techniques and subject-peripheral technology. The use of a technique is creative in the sense that the subject shapes the outcome by engaging closely in the process of production, guiding the activity step by step (Ingold 2000, p. 321). Technology, on the other hand, separates knowledge from practice. It is possible to distinguish between people who know and design, and those who put the designs into practice. Hence the latter, the subject utilizing the technology, mechanizes. Her/his opportunity to create, rather than just execute, diminishes. As a result, the further we move from a subject-central model of agriculture and forestry, the less the producers can control the boundary conditions of the developmental system of which they are a part, and the more dependent they become on a faceless techno-system.

However, what makes things more complicated is the dissipative and open nature of developmental systems. They are “islands of new order in the sea of disorder” (Urry 2005, p. 4). A spatio-temporal order necessarily interacts with the surrounding “sea”, blurring the boundary between inside and outside. Thus it is impossible to draw sharp distinctions between participants and non-participants. People and GM plants are bound to relate to each other through many kinds of “partial connections” (Strathern 2004).

On the other hand, GM plants do create very real and influential demarcations. They evince expectations and re-create rural spaces to suit their existence. Acknowledgement of this opens up prospects for “collective experimentation” (Latour 2004); for the comparison of existing collectives and the scripts proposed by the wannabe cultivars. It is clear that GM plants, as sources of im/possibility, fit well into some orders of farming and forestry while conflicting with some others. Experimentation is to tell where the limits actually lie; to what extent the scripts proposed by the organisms can be modified or ignored; and what the reorganization of pre-existing associations would imply for the development of possibility space.

By emphasizing the role of systemic interaction, the developmental systems view points out that uncertainty and vulnerability of a cultivation technology lies largely in the processes and patterns crucial for dynamic stability. It cannot be reduced by studying GM plants in isolation. In fact, it makes little sense to promise exhaustive certainty and controllability over entrainment and self-organization in the first place (see also Wynne 2005). This means that the uncertainty is not only epistemological but also ontological in nature (Kwa 2002).

Uncertainty underlines the value of local possibility space. Such a space can adapt to internal discontinuations and to outside stimuli. Conversely, limiting local action increases vulnerability by dissociating knowledge and power from local practice and by delegating it to commercial and administrative centers.

7. Conclusions

The key claim of this paper has been the fruitfulness of the developmental systems view in the study and evaluation of genetically modified plants. What is specific about the view is its stress on multi-scalar, systemic interaction. However, before the concept can operate as a useful analogue model for stabilization, it must be supplemented with a perspective that allows us to treat developmental systems as emergent and dynamic orders. The concept of entrainment does this. As a result, it becomes possible to see how organisms, as sources of novelty, can survive only if they synchronize with the temporal rhythms and spatial relations necessary for their growth. In this process, humans must naturally become entrained, too.

Entrainment connects and makes things possible, but as a precondition it also builds boundaries; impossibilities. Moreover, opportunities opening up through entrainment seldom materialize or survive without the emergence of new boundaries or restrictions. Therefore stability does not necessarily equal success. By referring to the concept of possibility space I have sought to emphasize that the empowering or suppressing consequences of a technology depend significantly on the qualities of the dynamic order that stabilizes along with it. Finally, im/possibilities do not spread evenly. For example, to escape, but still to live in a relationship with a GM standard may constrain action without liberation from any existing limits.

The official definitions of risk, included e.g. in EU Directives, ignore systemic interactions and implications. The inclusion of such effects would require a heuristic shift that allows replacing, or at least supplementing, of technological essentialism with a perspective that allows us to study GM plants both as potential targets of mobilization and as inevitable im/mobilizers of human agency. Since orders analogous to developmental systems are complex and in non-linear relation to each other, it is fairly pointless to try to prove the feasibility or unfeasibility of GM crops in universal terms, or to predict the societal consequences of a variety from the point of view of a single, immutable essence. Stabilization multiplies the object of evaluation. While this paper has focused on the expectations of GM plants on a general, heuristic level, the same question is always worth posing when facing a new candidate willing to associate with the world.

Acknowledgements

This paper originates from a course on complex dynamical systems held by Professor Chuck Dyke at the University of Tampere, May 2004. In addition to Professor Dyke I wish to thank Professor Yrjö Haila for inspiration and advice. Kirsi Törmäkangas, Ruth McNally, Jussi Kauppila and Riina Heinonen offered valuable comments and help – I am very grateful for them. For the revision of the English of the paper I thank Virginia Mattila. The paper is an outcome of a project financed by the Academy of Finland (project 209197).