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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation 2 Scientific Assumptions and Premises Underpinning the Regulation and Oversight of Environmental Risks of Transgenic Plants This chapter concentrates on the theoretical and empirical underpinnings of the regulation of environmental risks of transgenic plants and the use of risk analysis to evaluate and manage those risks. The first section summarizes the committee’s approach to risk analysis. Two important roles are identified that risk analysis of transgenic crops must fulfill; it must support the decision-making process of regulatory agencies, and it must legitimize the regulatory process, creating public confidence that human well-being and the environment are protected from unacceptable risks. The second section examines in detail the scientific and logical bases for regulation. In developing an approach that can be applied to both transgenic and conventional crops, the committee endorses the findings of three previous National Research Council (NRC) reports. Transgenic crops do not pose unique categories or kinds of environmental hazards. The entire set of existing transgenic crops is not so different in kind that they pose environmental hazards unlike those caused by other human activities, including conventional crops and other agricultural activities. The committee finds, however, that specific types of transgenic and conventional crops can pose unique environmental hazards. Also, the committee finds that there are good arguments for regulating all transgenic crops. To be effective, such a regulatory system must have an efficient and accurate method for rapidly evaluating all transgenic plants to separate those that require additional regulatory oversight from those that do not. The third section examines several technical issues related to the underlying risk assessment models. The concentration is on these because
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation they provide a basis for risk assessment of transgenic crops and will frame discussion of the case studies in subsequent chapters. Evaluation of the risks of transgenic crops requires specifying a social and environmental context for the assessment. Depending on the choice of context, different risk comparisons may become relevant. Finally, several formalizations are suggested that could help clarify this dependence on context and enable a regulatory agency to develop formal procedures to learn from its experience to improve the regulatory system. RISK Risk is both an intuitively easy and a technically difficult concept to understand. On the one hand, people take risks all the time in daily life, and whether explicitly or not, people are constantly balancing these perceived risks against their needs and desires. Everyone knows it is risky to drive a car, have radon leak into the basement, ice skate, play blackjack, or swim in a lake. But the personal and idiosyncratic ways people have of dealing with risk in their own lives have only tenuous connections to how society as a whole should deal with risk. Personal perceptions of risk may not reflect reality. One person might not care about the risks of eating a fish bone, but another may care so much that she will not eat any fish. Because each of us has our own way of dealing with risk, how do we agree as a society? Volumes have been written on the technical aspects of risk. In the catalog of the National Academy Press alone, there are 184 titles related to risk. Two that are particularly relevant to this report are a 1983 publication, Risk Assessment in the Federal Government: Managing the Process, and a 1996 report, Understanding Risk: Informing Decisions in a Democratic Society. The 1983 report outlines a general approach to characterizing hazards, modeling exposure pathways, and quantifying the probability of injury. The 1996 approach argues that any attempt to assess risk involves a series of interpretive judgments and framing assumptions and suggests that democracy is best served when those affected by regulatory decision making can be as fully involved in making those judgments and assumptions as is practicably possible. This chapter addresses risk from both perspectives. The 1983 report’s approach is followed in using science to illuminate technical understanding of the environmental risks of transgenic crops. By following this approach, however, the committee has made several implicit interpretive judgments and framing assumptions, which the 1996 report suggests. Several of these are acknowledged as implicit judgments and assumptions, and by doing so, an alternative perspective can be developed for evaluating risk analysis of transgenic crops. Before developing these par-
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation ticular ideas further, some of the broader assumptions made here to understand risk should be mentioned. Risk is interpreted primarily as a combination of the probability of occurrence of some hazard and the harm corresponding to that hazard. This is both a highly technical and somewhat vague interpretation, involving the related ideas of hazard, occurrence, and some combining process. A hazard has the potential to produce harm, injury, or some other undesirable consequence. In saying a slippery road is hazardous, it is not meant that any harm or a car accident has occurred. It simply means that the road conditions could potentially cause an accident. In this case the hazard is a car accident, which may or may not happen. Likewise, if a transgenic crop has a hazard, it does not mean that any harm has or will occur. Hazard identification is one of the most subjective and potentially contentious elements of risk analysis. While this report is limited to a consideration of environmental risks, there is some ambiguity in deciding what is and is not an environmental hazard. Does this include or exclude the potential for adverse impacts on human health that are mediated by the environment (not directly by food consumption)? Does it include or exclude the potential for adverse impacts on farming practices and profitability? Is a nonspecific effect on habitats or ecosystems an identifiable hazard? Is an effect on an ecological process an environmental hazard? The characterization of hazards in this chapter reflects an answer to each of these questions. The occurrence of a hazard is a probability that the hazard would occur. This typically depends on many factors. The probability that an accident will occur on a slippery road will depend on how many cars travel the road, how fast they are going, how much they accelerate and decelerate, the skill of the drivers, and other factors. Clearly, these probabilities will be highly conditional on the environment and other details about the situation, and therefore they will be variable both spatially and temporally. Likewise, the probability that any hazard associated with a transgenic crop would occur is likely to vary spatially and temporally. In much of the literature on risk, the probability of occurrence is called an exposure probability, referring to the probability that people are exposed to the hazard. In this report the term exposure is frequently used as a shorthand notation for the probability that a hazard would occur. The combining of hazard and occurrence probabilities to characterize risk can be contentious, ranging from simple mathematical formulations to complex deliberative processes involving many people. The committee leaves this process deliberately unspecified, so that the range of formulations can be used as needed in the report. In its simplest form, risk can be understood as a weighted probability in which the probability of occur-
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation rence is weighted by the magnitude of the hazard. If you are a driver on the slippery road, your risk is a combination of the probability that you will have an accident and the severity of the accident. Presumably (hopefully) the probability of an accident rapidly decreases with the severity of the potential accident, and your risk, which combines across all possible accidents, will be small. If you were a road engineer, you would also average over all combinations of drivers to estimate the total risk for society on that stretch of road. The process of combining hazard and occurrence can become more complicated if some drivers are considered more important than others, so that the risks themselves are weighted by some social criterion reflecting this importance. This can become even more complicated if the weightings are determined by some social deliberative process. Risk characterization is another one of the most subjective and potentially contentious elements of risk analysis. Risks can be reduced by people’s actions, and risk management is an important concept used in this report. By managing risks, people can reduce them to such an extent that they are considered insignificant. For example, one can reduce his or her risk of an accident on a slippery road by slowing down or simply by staying home during inclement weather. Similarly, planting and harvesting transgenic crops in certain ways can reduce the risks associated with them. These methods are discussed in more detail later in this report. There are a number of aspects of risk that are not explicitly addressed in this report. The committee does not discuss methods for valuation of hazardous events in either economic or other terms. Consequently the committee does not provide a basis for comparative rankings of risks nor a basis for comparing expectations of cost or loss with expectations of benefit associated with commercialization of transgenic crops. Moreover, by emphasizing the possibility and probability of unwanted outcomes, the approach taken in this chapter excludes an interpretation of risk that lays stress on the novelty or unfamiliarity of actions taken (such as fear of the unknown) except insofar as a novelty or unfamiliarity complicates the estimation of risk. The committee’s concept of risk also does not imply that some hazards are ones for which agents could be held accountable, while others would be considered works of nature. Finally, the distribution of risks among different groups of people is not emphasized. While we are all concerned with the distributional aspects of risks and benefits, and they appear to influence the debates about the utility of transgenic crops, the focus in this report is on issues where this concern has less influence. Specifically, the committee’s focus here is on the roles that risk analysis is expected to fulfill in the discussion of transgenic crops and some of the implications thereof.
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation Roles of Risk Analysis Risk analysis has come to play at least two somewhat distinct roles in public discourse. It is often conducted by using scientific information to support decision making in a particular case (referred to as “decision support”). This decision support role presumes that the decision maker (an individual, a group, or an organization) is well defined and has the legitimate and uncontested authority to make a decision. Within this class of risk problems, there are circumstances where decision making consists of selecting from among several well-defined options, such as whether to allow the commercialization of a particular transgenic crop. In these situations, risk analysis often consists of anticipating unwanted outcomes associated with each option and measuring their probability should that option be taken. Much of the present regulatory structure for transgenic organisms in the United States takes this approach to risk analysis. In circumstances where the decision options are not clearly defined, the role of risk analysis is considerably more ambiguous because its role in helping to inform a decision is not clearly defined. Under such conditions, risk analysis could be used to help inform a decision maker of the general scope of a risk situation and outline potential opportunities for decision making. Risk analysis could be conducted to provide a general survey of hazards and the types of risk management decisions that might confront a decision maker. For example, the World Health Organization (WHO) recently conducted a scientific consultation to determine if indirect human health risks were mediated through the environment from the use of transgenic organisms. This consultation focused on hazard identification because if such hazards could be established, the WHO could use its authority on human health concerns (granted by the United Nations) to justify additional risk analysis. In addition to its role in decision support, risk analysis can serve to reinforce and legitimize the authority of a particular decision maker to exercise control over a given situation (referred to as “creating legitimacy”). There are a variety of circumstances where the predictive power and presumed value neutrality of scientific risk analysis are implicitly assumed to provide the “best” basis for decision making. A decision maker’s ability to produce scientific risk analysis in such circumstances can play an important role in creating legitimacy to set policy or determine a course of events. For example, member-states of the World Trade Organization (WTO) can exercise their legal authority to restrict trade in a good only when they can produce a scientific risk analysis documenting a need to restrict importation of that good. A case where the risk analysis was insufficient in restricting importation was observed with Australia being forced by the WTO to accept frozen Canadian salmon (or pay a
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation steep fine) in spite of serious risk of transmission of fish disease, because Australia was unable to produce a sufficiently quantitative risk assessment (Victor 2000). Risk analysis can create legitimacy in many extralegal contexts as well. Highly contentious, politically charged issues can be decided on the basis of raw power, whether through political power or public influence, with little regard to the facts. Scientific risk analysis, with its philosophical commitment to value neutrality, can be used to legitimize a decision-making process. In some cases, people may agree to support the outcome of such a risk analysis-based decision process even if it contradicts their own desired outcome (NRC 1996). Thus, risk analysis can be a powerful force to garner legitimacy in a decision process from diverse public interests. There are many points of tension between the use of risk analysis to create legitimacy and its use as a decision support tool. A risk analysis that is expected to help create legitimacy for decision making must meet different burdens of proof than a risk analysis conducted as a decision support tool. When used in decision support, the authoritative agent is already determined and therefore is free to accept, reject, or modify any of the assumptions or parameters that may have been established in developing any component of the analysis. For example, a decision maker could explore the consequences of weighting the effects of a pesticide on farmers and farm workers less than (greater than) the effects on the general public. It is, in part, the flexibility to adjust assumptions and parameters that makes risk analysis particularly useful in a decision support role. This flexibility allows the decision maker to explore the full range of possibilities before coming to a decision. In contrast, when risk analysis is used to create legitimacy, the potential decision-making agent may find that the choice of assumptions and parameters has a profound effect on the willingness of affected parties to recognize the agent’s authority to make a final decision. When it is crucial to gain the acceptance of interested and affected parties, the flexibility to adjust assumptions and parameters may be dramatically reduced or sacrificed altogether. Affected parties know that adjustment of such parameters can influence results in ways that favor one interest over another and may insist on fixing assumptions and parameters in a manner that substantially limits the usefulness of risk analysis techniques. Indeed, the role of risk analysis to create legitimacy becomes particularly perilous when the decision options under consideration are not well defined. The role of risk analysis in governmental regulatory agencies has become increasingly ambiguous. The legal decision-making authority of such agencies is generally established by specific legislation or administrative findings. Traditionally, officials in these agencies have viewed risk
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation analyses in the role of decision support for the exercise of this legislatively mandated authority. However, their freedom to adjust assumptions and analytical parameters in risk analyses may be constrained by the language of the authorizing legislation or by successful court challenges from affected parties. This suggests that to some degree risk analysis has already become a component in establishing a government agency’s legal authority to make determinations. A more serious source of ambiguity flows from the extralegal burdens that regulatory decisions are increasingly expected to meet. The regulatory process is often described as the basis for public confidence in the safety, reliability, and fairness of the regulation of transgenic organisms (Carr and Levidow 2000, Ervin et al. 2000). This confidence may be vested in the integrity and judgment of regulatory officials themselves, but many commentators have expressed the view that it is or should be based on the risk analyses alone. This way of describing public confidence implies that risk analyses must be capable of being seen to embody principles of objectivity, fairness, and rigor by the general public. This is a burden of proof that goes considerably beyond the ability to withstand a legal challenge, and it takes risk analysis well beyond its traditional role in decision support (Funtowicz and Ravetz 1990, Von Winterfeldt 1992). If risk analysis is expected to play any significant role in establishing the public’s confidence in genetically modified crops, it becomes crucial to examine the procedures and methods for conducting a risk analysis with two ends in mind. Finding 2.1: Risk analysis of transgenic crops must fulfill two distinct roles: (1) technical support for regulatory decision making and (2) establishment and maintenance of the legitimacy of regulatory oversight. Terminology of Risk Analysis Although there have been many attempts to standardize the terminology for describing the stages of risk analysis, these attempts seldom gain widespread acceptance. Such stages are only a heuristic device intended to facilitate a collaborative approach to problem solving with respect to risk. Thus, there is no one best set of terminology, and this report shifts among the various sets as the problem merits or demands. However, it is impossible to communicate the committee’s ideas clearly without a discussion of the various approaches to describing the stages of risk analysis. One of the most influential early studies on risk analysis uses the terminology of risk determination, risk evaluation, and risk acceptance to char-
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation acterize the stages of risk analysis (Rowe 1977). The general idea is that one must have an initial identification of the problem that the risk analysis is expected to address (i.e., risk determination). With a well-defined problem, techniques derived from the natural sciences and engineering are deployed in a process of risk evaluation (measuring and combining the magnitude of the hazard and the likelihood of its occurrence). Finally a decision maker makes a decision (i.e., risk acceptance). When risk analysis is used to support policy or contentious decisions, the simple three-stage characterization of risk analysis itself becomes controversial. Some have preferred to call the first stage hazard identification, implying that a hazard does not become a risk until the probability that it might occur has been measured. Some object to the normative connotations of the word evaluation and substitute the term risk measurement or risk assessment for the middle stage. Many have noted that risks may not be simply “accepted,” so the third stage is then relabeled as “risk management.” Because risk analysis of transgenic organisms is itself contentious, the committee chose to adopt the terminology hazard identification, risk assessment, and risk management when discussing risk in its decision support role. Broadly conceived, the techniques of risk assessment are of five general kinds: Epidemiological analysis. Events of interest are observed, and the statistical relations of these events in the sampled populations are analyzed. This epidemiological approach has been very effective in identifying disease risks among populations such as smokers, industrial workers exposed to certain substances, and persons with a specific genotype. The scientific rationale for this method is that empirical correlations provide a basis for predicting effects and may indicate cause. This method could be used to associate risks with particular transgenic plants that are intensively planted in large or specific areas. Theoretical models. A theoretical model that mimics or simulates the causal interaction of elements in a complex system is used to identify likely sources of system failure. This approach is widely used to study the risk of failure in engineering contexts such as instrumentation and control design. It has also been applied in biology to develop strategies for ecosystem management. The scientific rationale for this method is that it provides the logical consequences of a set of scientific assumptions about risks. It has played a critical role in analysis of the risk of evolution of resistance to transgenic insecticidal plants (Alstad and Andow 1995, Roush 1997, Gould 1998), and could play a role in evaluating community-level non-target effects of transgenic plants (Andow 1994). Experimental studies. Controlled experiments are conducted to iden-
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation tify cause-and-effect relationships. Variations on this approach (often combined with statistical analysis) are used in product testing, including clinical trials for drugs and therapeutic devices. The scientific rationale for this method is that it establishes the cause or causes of a risk. Laboratory experiments can be used to establish a potential hazard (Hilbeck et al. 2000), and field experiments can be used to evaluate potential risks (e.g., Orr and Landis 1997). With field experiments, however, it is necessary to guard against false negatives (type II statistical errors), which would lead to concluding erroneously that there is no risk when, in fact, the experimental design is incapable of detecting any risk except a very large one (Marvier 2001). Expert judgments. A group of experts use personal knowledge of a given system to estimate likely system performance under untested conditions. This is a widely used approach in risk analysis and has become the basis for risk analysis for some invasive species in the United States (Orr et al. 1993). The group is chosen to represent a range in necessary expertise with due consideration to potential conflicts of interest. The scientific rationale for this method is that the consensus of the group of experts represents a synthesis of the best-available scientific knowledge on the risk (Jasonoff 1986). The Environmental Protection Agency (EPA) uses this method frequently to aid in risk assessment of transgenic plants in its SAP (Scientific Advisory Panel) process, and the U.S. Department of Agriculture’s Animal and Plant Health Inspection Service Biotechnology, Biologics, and Environmental Protection unit (USDA-APHIS-BBEP) has used it to evaluate the initial notification system for transgenic plants (USDA-APHIS 1993). Expert regulatory judgment. Regulatory personnel use personal knowledge of a given system to estimate likely system performance under untested conditions. This is the most widely used approach in risk analysis. The scientific rationale for this method is that regulatory personnel have ready access to confidential business information and understand both current scientific knowledge and the process of risk analysis, so their judgments can be rendered with minimal delays and sufficient scientific accuracy. This is the method used by USDA-APHIS-BBEP to evaluate most of the complex, difficult-to-measure potential risks associated with transgenic plants. The first three of these approaches are generally accepted as scientifically rigorous methods of analysis. Expert judgment, whether by external experts or by regulatory judgments are less rigorous, but often acceptable. A consensus of multiple external experts is likely to be more rigorous than the expert regulatory judgments because disagreements among external experts are likely to lead to more robust risk assessments (Jasanoff 1986).
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation Finding 2.2: At least five standards of evidence can be used in a risk assessment for decision support. The scientifically rigorous methods include epidemiological, theoretical modeling, and experimental methods. A consensus of multiple external experts is likely to be more rigorous than the expert regulatory judgments. Finding 2.3: More rigorous methods used in decision support are likely to help risk analysis fulfill its other social role of establishing and maintaining regulatory legitimacy. Chapter 5 evaluates circumstances in which these various methods should be used to supplement or displace expert regulatory judgment. In addition, for some questions the committee suggests specific types of data that should be collected to support epidemiological analysis, the simulation models that should be developed, the experimental studies that need to be conducted, and when expert panels should be convened. Implementation of any of these approaches (alone or in combination) requires a process to clarify the role that each general technique will play in measuring risk. Risks may spark public outrage, and a fourth stage of risk communication has been suggested. But in the decision support role of risk analysis, communicating with the public may actually just be a tool of risk management, so the committee treats risk communication as a subset of risk management when discussing risk analysis in its decision support role. However, in its role of creating legitimacy, the greatest source of disagreement over risk often concerns the early stages of conceptualizing and identifying risk. Because some models of risk communication can become a way to exclude affected parties from this crucial part of the process, the 1996 NRC report considers risk communication integral to all stages of risk analysis. While inclusion in all stages blurs the category of risk communication, it must be integrated with all stages of risk analysis, and affected parties must be brought into early discussions. When this is done, the three-staged framework of risk analysis also becomes less useful. For example, hazard identification is no longer an exercise in listing potential hazards but becomes a deliberative process from which potential hazards are characterized. Moreover, even when science and engineering methods are used to measure the probability that these potential hazards will materialize into bona fide risks, the risk problem is substantially sharpened and redefined by deliberative processes, so it seems appropriate to include this part of risk analysis under the heading of risk characterization as well. Clearly, the stages of risk analysis do not, in fact, represent temporally, analytically, or even conceptually
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation distinct and discrete elements. These considerations led the 1996 NRC report to describe risk characterization as: the outcome of an analytic-deliberative process. Its success depends critically on systematic analysis that is appropriate to the problem, responds to the needs of the interested and affected parties, and treats uncertainties of importance of the decision problem in a comprehensible way. Success also depends on deliberations that formulate the decision problem, guide analysis to improve the decision participants’ understanding, seek the meaning of analytic findings and uncertainties, and improve the ability of interested and affected parties to participate effectively in the risk decision process. (158) In the role of creating legitimacy, deliberation is central in risk characterization. It is important at every step in the process of making risk decisions, and must be incorporated into each stage of risk analysis. Therefore, when discussing risk in its role of creating legitimacy, this committee chooses to adopt the terminology risk characterization, which seamlessly integrates processes involved in hazard identification, risk assessment, and risk management. Hence all these processes are better thought of as integrating subcomponents of risk characterization rather than steps in a risk analysis process. Risk Analysis as Decision Support in the Regulation of Transgenic Plants Since the use of transgenic crop plants was first discussed, there has been confusion over the basis for distinguishing between the potential environmental risks associated with these plants and the risks associated with conventionally produced plants. As the power of conventional plant breeding has increased over the past 50 years, there has been a corresponding increase in the kinds and number of traits that can be bred into a commercial variety. As reviewed in Chapter 1, these changes and concomitant changes in agricultural production systems have created opportunities for novel interactions between agriculture and the surrounding organisms, habitats, and ecosystems. Transgenic crops are the latest development in this trend. Consequently, it is important for regulatory agencies to pay heed to the possibility that transgenic crops will be involved in novel ecological interactions resulting in novel environmental risks. A series of scientific studies and reports have consistently found that the risks associated with a crop variety are independent of the means by which the crop was created. A 1987 NRC report concluded that the environmental risks associated with transgenic organisms are “the same in kind” as those of the unmodified organisms or organisms modified by other means. A 1989 NRC report clarified this statement to argue that this
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation Finding 2.14: There are typically multiple reference scenarios that are appropriate in assessing the risks of transgenic crops. Characterizing the Transgenic Organism There are several approaches to characterizing the transgenic organism for comparing risks. In the United States, APHIS divides the transgenic organism into two parts—the unmodified organism and the transgene and its products. The hazards associated with these parts are identified, and the likelihood that the hazard will occur is assessed using a simplified fault-tree analysis (Lewis 1980, Haimes 1998). One alternative to this two-part model is a whole-organism analysis. And in addition to the fault-tree approach, an event-tree analysis also is considered. These appear at first to be very subtle distinctions, but they lead to a different structure in the risk analysis. Two-Part Model In the two-part model the transgenic plant is conceptually divided into (1) the unmodified crop and (2) the transgene and its product. The risk assessment then evaluates the risk of the unmodified crop separate from the risks associated with the transgene and its products. For example, a herbicide-tolerant soybean would be evaluated as an untransformed soybean plant for which no environmental risks have been found and as the appropriate herbicide resistance gene and its transcribed product or products (see other examples in Chapter 4). The theoretical rationale for this approach is that the transgene is a small genetic change that is likely to have only a small phenotypic effect. Therefore, the untransformed soybean is unlikely to be changed very much and provides a good baseline comparison for understanding the risk of a transgenic plant. The transgene itself is considered an incremental change in the soybean, and its risks are assumed to be able to be assessed independent of the soybean. After these assessments are completed, the whole transgenic organism is assessed to determine if there are any additional hazards that would require assessment. If so, appropriate reference comparisons are developed. Conceptually, this reductionist methodology attempts to identify and assess most of the risks in the initial step. The final step is to pick up any residual effects stemming from any interactions between the trait and the untransformed organism that require additional assessment. The two-part model makes a procedural commitment to making the untransformed crop plant the central reference scenario for contextualizing the risks of a transgenic crop. As discussed below, to evaluate the effect of the transgene, the most scientifically revealing comparison is the
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation transgenic variety and its near-isogenic non-transformed parent. However, near-isogenic lines are not always available to allow the best scientific comparisons to be made. In addition, the two-part model has not used some alternative reference scenarios, such as a range of cropping systems or alternative approaches to accomplishing similar production or environmental goals as the transgenic crop. Finally, the two-part model assumes that single gene changes have small ecological effects. As discussed in Chapter 1, this is not always the case. Whole-Organism Model In a whole-organism model, the reference comparisons to the whole transgenic organism are developed at the beginning of the risk analysis. This opens up the scope of reference comparisons to include some that might not be considered under the first model. This model does not require that all risks are assessed using a whole organism; this is a conceptual model that provides an approach for identifying appropriate hazards and reference scenarios. For example, under the two-part model, Bt corn was assessed by considering first the unmodified corn plant and the Cry toxin. Because corn was considered to pose insignificant environmental risks, it has been dismissed routinely as a risk. Cry toxins were evaluated for their insecticidal properties during the registration of B. thuringiensis as an insecticide, and these evaluations were used to assess the risks of the toxin. The appropriateness of this comparison can and has been challenged, in that where APHIS found no hazards in its initial assessments (see Chapter 4), EPA identified the evolution of resistance in the target pests to the toxin as a hazard. In posing the question of whether there are any additional hazards arising from the interaction of the transgene and the plant, relatively few hazards have been identified, perhaps in part because the methodology has not been firmly established. In general, as shown in Chapter 4, APHIS relies on an analysis that is based on comparing the transgenic crop to a conventional crop with a similar phenotype. If a similar phenotype can be identified, APHIS contends that because the conventional crop phenotype has a record of safe use, the transgenic crop plant is expected to be safe too. In the case of Bt corn, APHIS compared the transgenic crop to other insect-resistant corn varieties because no conventional Bt variety exists. While the validity of such comparisons can be challenged (see Chapter 5), the method is consistent with the two-part model. A whole-organism model would initially focus on identifying the potential hazards associated with the transgenic crop variety. The appropriate reference scenario for hazard identification may include the untransformed crop and conventionally produced crops with comparable
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation phenotypes, which are used in the two-part model, but risk comparisons are not restricted to these two scenarios. For example, the transgenic crop will be expected to replace other agricultural production systems and possibly some nonagricultural native or natural habitat, and it may affect neighboring agricultural and nonagricultural habitats. Hence, the risks associated with a Bt corn might be compared to corn sprayed with insecticides in the irrigated regions of northeast Nebraska because it might be expected to replace this production system at that locality. In Minnesota, Iowa, Illinois, and the rest of Nebraska, Bt corn might be logically compared to an unsprayed conventional crop. In a similar way, Bt poplar might be compared to conventional poplar plantations sprayed or not sprayed with insecticide, but because it might lead to an increase in area planted to plantation poplar, it could also be compared to the risks associated with second-growth forest, which it might replace. In addition, because Bt corn might affect neighboring organic farmers through contamination via cross-pollination, and Bt poplar might affect the ecological functioning of neighboring forest and savanna ecosystems, these ecosystems might also be appropriate reference scenarios. The theoretical rationale supporting the whole-organism model is that the risks and hazards associated with a transgenic crop plant occur as a result of the trait in the crop plant in a particular environment. The risks and hazards do not occur from the trait separated from the crop plant separated from the environment. Comparison of the Two-Part and Whole-Organism Models In principle, the two approaches should end up with the same characterizations of risk, but in practice they probably will not. The two-part model addresses whole-plant concerns in its second step and should therefore capture all hazards and risks at this stage. The methodology used in the second step of the two-part model, however, must be different from the whole-organism model because if it were the same, the first step would not be necessary. It is in this difference that the models probably diverge. There are potential biases in the two-part model, which may underestimate or overestimate risk. The initial step of dividing the organism and evaluating the risk of the parts may lead to an underestimation of risk when the parts are found to have no significant risk and, vice versa, may lead to an overestimation of risk when the parts are considered risky. This is because these initial findings are likely to influence subsequent investigations used in the second step. If no significant hazards or risks are characterized in the initial step, it may be difficult operationally to justify and sustain a lengthy second step risk analysis. Conversely, an initial finding of risk may unleash a cascade of additional investigations, perhaps leading to an overestimation of risk.
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation Risk Assessment Models Risks can be assessed in numerous ways, with various assumptions and biases. Transgenic crops have been assessed in the United States by APHIS utilizing a rigid risk analysis framework that lacks a formal approach for detecting potential for mistakes. Certainly the system is designed to limit mistakes, but mistakes do occur, and their significance is unknown. Two different analytical frameworks are discussed below that could be used to supplement present risk assessment practices—a fault-tree analysis and an event-tree analysis (Lewis 1980, Haimes 1998). Fault-tree analysis can be used to investigate potential risk. For example, one can hypothesize that Bt corn adversely affects some non-target organism. A fault tree could lead the analyst to investigate thoroughly all potential causal pathways. Fault-Tree Analysis Fault-tree analysis logically evaluates risk by tracing backwards in time or backwards through a suspected causal chain the many different ways that a particular risk could happen (Lewis 1980, Haimes 1998). The analysis is conditioned on a given hazard, that is, the analyst must have a particular hazard in mind before the analysis can be conducted. This is both its strength and its weakness. It is a strength because the analysis focuses on the ways that risks occur and does not waste time evaluating the ways that risks do not occur. By concentrating on the known hazards, the analysis provides a comprehensive and efficient methodology for assessing risk. It is a weakness because unknown or unanticipated hazards cannot be evaluated simply because they have not been identified. Because the hazards associated with complex systems cannot all be unambiguously identified ex ante, this is its most serious weakness. Figure 2.4 is a simplified fictitious example of a fault-tree analysis of the risk of Bt corn to a non-target insect species. The total risk is a weighted “or” gate of the risks in cornfields, near cornfields, and far from cornfields, where the weight is the relative proportion of the insect population in each habitat area (in the example in Figure 2.4 these weights are equal). In an “or” gate the risk would occur if any one of the inputs occurs, and in an “and” gate the risk would occur only if all of the inputs occur. This risk calculation is detailed for risks to the species inside cornfields, which is an “or” gate of the risks associated with each of the three most common transformation events in Bt corn. This risk, in turn, is an “and” gate of the probability that monarchs are in Bt corn of the specific event and the probability that they will be killed by pollen from the event. This box is further detailed for Event 176, in which mortality is related via an “and”
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation FIGURE 2.4 Simplified fictitious fault-tree analysis of the risk that individuals of species X are killed by the sum of three varieties of Bt corn (V1,V2,V3). This fault-tree traces backwards through the causal chain. In this example the logical structure of the model is Boolean algebra, which consists of “gates” that indicate how the faults lower in the tree should be combined to estimate the probability of occurrence of the higher levels in the tree. The upper levels of the tree consist of “or” gates (the pointed arrowheads). An “or” gate signifies that if any of the input statements are true, the output statement is true and therefore the inverse of the product of the inverse of the input probabilities can be used to compute the output probability, assuming the input statements are independent. The lowest level consists of “and” gates (the half-rounded symbols). An “and” gate signifies that all input statements must be true before the output statement is true, and therefore the product of the input probabilities can be used to compute the output probability. p values in the figure are entirely fictitious and are provided for illustrative purposes.
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation gate to the probability that the species is exposed to the Bt pollen and the toxicity of Event 176 pollen. Fault-tree analysis is often used to assess the risk involved in potential failures of the safety system itself. This tradition is well developed in the aeronautics industry, where airplane safety and safety systems are subjected to rigorous fault-tree analyses (Lloyd and Tye 1982). A simplified fault-tree model for the safety system associated with APHIS regulation of transgenic crop plants is illustrated in Figure 2.5. This emphasizes one potential adverse effect that could occur through failure in the present oversight system. Although conducting such an analysis would require too much effort for this committee to complete, the elements of such an analysis are discussed in Chapter 5. Clearly, conducting such an analysis FIGURE 2.5 Simplified fault-tree model of the risk that a commercialized hazardous transgene product enters the human food chain via the environment. The logic is Boolean logic as in Figure 2.4, except that in this tree all the gates are “or” gates. This fault tree focuses on the possibility that the risk occurs because of failures in the safety network. Most industries with safety systems to manage risks analyze the potential failure of the safety system itself. This kind of analysis has led to the development and implementation of “fail-safe” systems, such as in the aeronautics industry.
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation would provide a regulatory agency with considerable information to improve its regulatory procedures and could contribute to a more formal methodology for a learning system in an agency. The cost of such an analysis is unknown. Event-Tree Analysis In contrast to fault-tree analysis, event-tree analysis logically works forward in time or forward through a causal chain to model risk (Lewis 1980, Haimes 1998). Event-tree analysis is not conditioned on the existence of a known hazard. Starting with an initiating event, the next steps in a logical chain of events can be assessed until the risk probability associated with a hazard can be calculated from the probabilities associated with the chain of events. Interestingly, event-tree analysis does not have to be aimed at estimating the risk associated with a particular hazard. Event-tree analysis can be initiated to investigate an entire category of hazards, during which the risk associated with particular hazards is assessed. If the processes in a complex system are understood well enough, event-tree analysis can identify hazards by following the complex sequence of events to their logical conclusions. For example, an event chain analysis of the potential non-target risks associated with a transgenic crop producing a toxin could begin quite generally, because we know the toxin that would cause any of the nontarget risks that could occur (see Figure 2.6). Consequently, an event-tree analysis of non-target effects can be initiated through a toxin fate and transport analysis, tracking where and when a toxin goes until it is degraded into nontoxic forms. If there is enough information, such a fate and transport analysis could reveal when apparently independent pathways converge to allow toxin to concentrate in some part of the ecosystem. For Bt corn, the first step in the event-tree analysis requires understanding what toxin is expressed in the plant, where and when it is expressed, and how that toxin might reach the environment. All Bt corn varieties produced a truncated Cry toxin, which is significantly smaller than the protoxin produced by the bacterium. It is hypothesized that truncation may alter the host specificity spectrum, creating novel nontarget risks dissimilar from Bt insecticides (Jepson et al. 1994, Hilbeck 2001, but see MacIntosh et al. 1990). The toxin is expressed in all of the plant tissues when the plant is actively growing, with variation among the transformation events. The toxin moves in the pollen and remains in the dead plant tissue after senescence. In Bt corn, truncated Cry toxin can enter the soil via root exudates (Saxena et al. 1999), exposing soil organisms. The activated toxin readily binds to montmorillic clay particles and
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation FIGURE 2.6 Simplified event-tree analysis of the non-target risk of a toxin produced in a transgenic plant. Event-tree logic is based on a chain of mutually exclusive events. An event tree begins with an initiating event and follows the consequences of the event through a chain of subsequent events, assigning to each branch a probability of occurrence. The end result is a long list of the possible consequences of the initiating event in which each consequence has associated a certain probability of occurrence. The sum of the probabilities at a level of the tree, SiPWi = 1 (here W = A, B, C, or D), that is, PA1 + PA2 + PA3 = 1. The branches for many of the lower boxes are incomplete. Non-target species s could be affected through multiple causal chains, so the overall effect of the toxin on species s may be a complicated aggregation of these effects. This event-tree analysis also is initiated by a general event that would be common to many non-target hazards. The specific hazards to particular species are evaluated later in the analysis.
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation can retain insecticidal activity for more than nine months (Saxena et al. 2000). The untruncated protoxin in Bt insecticides does not readily bind to clay and is degraded rapidly in soil (Venkateswerlu and Stotzky 1992). Consequently, Cry toxin from Bt corn has several unique exposure pathways not characteristic of either corn or the toxin from bacteria. Each of the potential pathways can then be assessed to determine if there is a potential hazard associated with them; if so, the risk can be characterized by choosing an appropriate reference comparison for that exposure pathway and potential hazard. Event-tree analysis may become particularly useful when risks associated with transgenic crops with many traits are characterized. Finding 2.15: The two-part model may bias a risk assessment either toward a finding of no significant risk or a finding of significant risk. As presently implemented, the former bias may predominate. Finding 2.16. Additional research is needed to evaluate the utility of the whole-organism model and a more formal use of fault-tree and event-tree analysis. Experimental Comparisons Plant breeders and geneticists make a variety of comparisons using appropriate statistical designs and analyses. New varieties of crops are not generally released for large-scale use until a variety review committee reviews the data. In the case of transgenics a single gene is introduced into cells growing in tissue culture, and the regenerated plant displaying the trait is backcrossed several generations to an elite line. A reasonable genetic comparison for risk assessment is the untransformed elite line. For example, six backcrosses should produce progeny that are genetically over 99% identical to the elite line used as the recurrent parent. This value of 99%, however, is an average or expectation and is not always reached. The ideal comparison of a transgenic following backcrossing is to its near-isogenic line derived by self-pollination of plants heterozygous (hemizygous) for the transgene in the most advanced backcross generation. This will give plants homozygous for the transgene as well as plants without the transgene; all unlinked regions of the genome will segregate independently of the transgene locus and should not influence comparison of the two homozygous lines derived from the homozygous plants. This comparison is not absolutely perfect because the transgene chromosome likely will carry a genomic region on each side of the transgene from the transgenic parent. However, this comparison is theoretically the best available.
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation If near isogenic lines are not available the only possible comparisons are among unrelated plant lines. In such comparisons it will always be difficult or impossible to determine if an observed difference between the plant lines was caused by the insertion of the transgene or was simply due to another genetic difference between the two plant lines. Conversely, if no difference is observed, it will always be difficult, or impossible to determine if the transgene had no effect or if other genetic differences masked the effect of the transgene. The committee recommends that near-isogenic lines with and without the transgene be developed and evaluated as part of the process of risk analysis. In addition, a way should be found to make such near-isogenic lines available for study by public scientists. The availability of such genetic materials would substantially strengthen comparisons, save time and money, and provide much more legitimate comparisons. The potential to mislead the public—positively or negatively—is too great unless the best-available genetic materials are used. Clonally propagated crops can be readily compared to transgenic versions. Self-pollinated crops raise most of the same concerns expressed above for cases where backcrossing is involved. If backcrossing is not the breeding scheme, the process of advancing the materials must be considered to determine the most appropriate comparisons. Finding 2.17: For certain questions, the availability of near-isogenic lines can allow scientifically legitimate comparisons and facilitate the assessment of risk. CONCLUSION This chapter has reviewed general approaches and roles of risk analysis, the scientific, social, and logical bases for regulation of transgenic plants, and some technical issues related to the risk assessment process itself. It explains that risk analysis typically must fill two roles: providing technical information to decision makers, and creating confidence among stakeholders in the risk analysis process. The specific importance of the second role in the risk analysis of transgenic plants is discussed. The use of the most rigorous scientific approaches in conducting risk analyses is critical for both roles of risk analysis. Because there is no way to evaluate the risks of transgenic plants without empirical examination, there is a scientific reason to examine the characteristics of transgenic plants on a case-by-case basis. Although there has been a general assumption that the products of conventional plant breeding are safe, while products of transgenic processes could pose envi-
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Environmental Effects of Transgenic Plants: The Scope and Adequacy of Regulation ronmental risks, this chapter and others in the report find no logical or scientific support for this assumption. Environmental assessment of transgenic crops relies on risks associated with the transgenic variety being compared with multiple appropriate reference scenarios (ways to accomplish the same goal). For example, the risks associated with a transgenic herbicide-tolerant variety could be compared with risks of chemical weed management used on nontransgenic varieties, cultivation practices, crop rotations, and other approaches for weed management. This chapter ends by pointing out that there are a number of general approaches for formally examining a risk analysis to determine where errors could occur. These formal examinations could be helpful in assuring the rigor of the current system used for transgenic plants.
Representative terms from entire chapter: