Biotechnology Risk Assessment: a View from Plant Pathology1

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Chapter33 Biotechnology Risk Assessment: A View From Plant Pathology1

X. B. Yang

biological systems elevates the potential for ecosystem impacts. Some propose that genetic engineering could cre Introduction ate ecologically high-risk, super-competitive organisms that could alter ecosystem function. Biotechnology has Agricultural science has established a framework for bio generated new concepts and potentials for modifying bio logical impact assessment through past work. Various risk logical systems. Biological scientists are asked to design assessments for diverse areas of agriculture, resulted in an predictable biological systems for human needs while sus accumulation of considerable information. Baseline infor taining natural resources (Fulkerson 1987). Many biologi mation for biological impact assessment dates from the last cal science disciplines assess potential ecosystem impacts century (Fulkerson 1987). One type of biological impact from genetic engineering technology. Forestry initially fo assessment is the environmental impact assessment on the cused on poplar, an agricultural crop grown worldwide release of transgenic poplar. Plant pathologists played a for fiber, energy, and wood production, to assess the im major role in an early experimental release of transgenic pact of biotechnology on the environment (Klopfenstein poplar (McNabb et al. 1991). Plant pathology has provided et al. 1991, 1993; McNabb et al. 1991). much of the information for developing biological impact Biological impact assessment estimates the potential or assessment (Teng and Yang 1993) with a focus on complex actual impact, including hazards and benefits, of the pres microbe-related risk assessments. This paper discusses bio ence, introduction, or entrance of specific organisms into logical risk assessment for woody plants compared to her a biological system. Impacts can arise from the introduc baceous crops, specifically: 1) the need for and status of tion of any new technology into a natural ecosystem, risk assessment; 2) risk assessment concepts; and 3) risk whether a physical product or knowledge-based process. assessment methodology. All impacts should be assessed. In microbial ecology, issues regarding testing and ap plication of biotechnological products are frequently dis cussed (GilJett 1986; Lindow et al. 1989; Turgeon and Yoder 1985). Because of the nature of plant pathogens, and be Need for and Status of cause microbes form the lower trophic levels of most eco Risk Assessment systems, genetic engineering of organisms has been considered a risk to ecosystem stability. This potential for environmental risk is associated with the: 1) creation of a Biotechnology has changed some sectors of agriculture new pest; 2) enhancement of existing pathogens through into industries perceived as high risk and high return. The gene transformation; 3) harm to nontarget species; or 4) increasing ability to manipulate genetic components in any other ecosystem disruption. Early environmental im pact assessment of transgenic microbes involved the po tential application of non-ice-nucleating bacteria to prevent frost injury in California (Andow et al 1989; Lindow et al , Klopfenstein, N.B.; Chun, Y. W.; Kim, M.-S.; Ahuja, M.A., eds. 1983; Lindow and Panopoulus 1988). Currently, some epi Dillon, M.C.; Carman, R.C.; Eskew, L.G., tech. eds. 1997. demiological studies concern horizontal gene transfers in Micropropagation, genetic engineering, and molecular biology microbes such as those using Colletotrichum spp. for bio of Populus. Gen. Tech. Rep. RM-GTR-297. Fort Collins, CO: logical weed control (TeBeest et al. 1992). U.S. Department of Agriculture, Forest Service, Rocky Mountain The environmental impact of transgenic woody plants Research Station. 326 p. is a major issue in the development and application ofbio-

264 Biotechnology Risk Assessment: A View From Plant Pathology

technology. A concern of risk assessment is the potential cently, risk assessment was defined as a process to deter for transgenic plants to displace native species (Duchesne mine and evaluate potential risks, and the magnitude and 1993; Pimentel et al. 1990; Rogers and Parkes 1995; Teng probability of those risks occurring (Teng and Yang 1993). and Yang 1993; Tiedje et al. 1989). Similarly, the potential There are 2 steps in risk assessment: 1) risk determination, of transgenic woody plants to replace wild flora is also a which is identifying and characterizing the risk source; and major concern. The need to assess the biotechnological 2) risk estimation, which is estimating the probability and impacts on nontargeted pests and nonpests, and the po magnitude of adverse effects from an introduced organ tential threat this poses to forest ecosystems has been dis ism in an ecosystem (figure 1). Biotechnology-related im cussed (Duchesne 1993). Unfortunately, assessing the pact assessment is concerned with the estimation of environmental fate and impact of transgenic trees lags potential or actual consequences after introduction of behind the ability to create them. Methods are needed to transgenic products into an ecosystem. Risk assessment assess the environmental impact of transgenic trees to before field testing may be premature unless the risk is safely incorporate them into forestry research and silvi known (Teng 1991). culture. Biotechnology-related risk concerns hazards that are Risks associated with transgenic plants have been ex negative acts or events in quantitative terms with the prob tensively discussed (Gould 1988; Pimental et al. 1990; ability of risk. In this concept, risk assessment includes: 1) Tiedje et al. 1989). In 1987, transgenic tomato plants were identifying the hazard; 2) characterizing the risk; and 3) the first field-tested, genetically engineered, food crop managing the risk. The first 2 steps are similar to the risk (Muench 1990). A gene encoding the coat protein of to determination step previously mentioned. Risk; in both of bacco mosaic virus (TMV) was introduced into tomato the above contexts, is used in plant pathogen-related as plants for virus resistance. Risks associated with such a sessments; however, the concept of risk changes with the release are the potential formation of a virus with altered discipline or situation. For example, risk is also consid vectors and new host ranges and the possibility of new ered the product of probability and the impact of a haz gene combinations (Zoeten 1991).Alternatively, such new ard, where hazard is any undesirable event (Evenhuis and combinations will likely occur less than that in nature (Falk Zadoks 1991). and Bruening 1994). In other countries, various transgenic "Monitoring," repetitive measurements made to specify agricultural plants are at different stages leading up to the state of a system over time, does not include the data field tests (e.g., tungro-resistant rice and virus X-resistant interpretation. Monitoring can provide a "time series," potato). In the scientific community, a consensus is emerging on how much biosafety is needed. However, until a common policy is agreed upon, countries will continue to have dif fering guidelines. Transgenic hybrid poplar trees were used Risk Determination as an early first field test to assess the risk of transgenic woody plants (McNabb et al. 1991). The risk of harmful gene transfer via pollen dispersal was considered + (McPartlan and Dale 1994; Sawahel1994; Williamson 1993). Data and Information Database J A procedure to assess such risk was proposed in the Neth Generation "-----_.( erlands (Evenhuis and Zadoks 1991). However, method ology has not been developed. Teng and Yang (1993) + proposed an outline for assessing the microbe-related risk on herbaceous crops. A conceptual risk assessment out System Synthesis line includes the common principles of impact assessment from different specializations, many of which are appli y cable to risk assessment for a woody crop such as poplar. + ( Prediction - GIS ~ l i_ ~c~ Concepts of Risk Assessment Risk Interpretation l...tiv The National Academy of Sciences (1983) defines "risk assessment" as the use of scientific methods, models, and Figure 1 . Schematic of risk assessment process in the data to develop information about specific risks. More re- context of biological impact assessment.

USDA Forest Service Gen. Tech. Rep. RM-GTR-297. 1997. 265 Section V Biotechnological Applications

which is a collection of observations made sequentially in bility to prediction; and 3) be sensitive to hazard. The early time to obtain "background" or "baseline information" field-test of transgenic poplars at Iowa State University (Duniker 1989). The background or baseline information had a well defined operational endpoint, which was to is a description of conditions or dynamics existing in an measure growth of transgenic poplars in comparison to ecosystem before an intervention, such as introducing a nontransgenic poplars under field conditions (McNabb et genetically engineered microbe (GEM), and serves as a al. 1991). check for any assessment. Statistically, a system baseline may be the inherent variability of an ecosystem. By using different statistical techniques, such as a time-series analy sis, variability of system output can be partitioned into inherent variability (regular pattern) and noise. For ex Assessment Methodology ample, Jacobi and Tainter (1988) reported a time series of drought affects on loblolly pine growth measured as re Risk Determination duced annual increment compared with the healthy sta tus. The pine trees, measured annually for 60 years, showed To efficiently assess a risk, ecosystem components at the a declining growth rate in the first 30 years, followed by a individual, population, or community level must be out growth rate increase then a decrease again. Tune-series lined to define outputs and endpoints. Well-defined out analysis detected a 3-year periodic pattern in the data puts and endpoints sharpen research objectives by (Yang, unpublished). Patterns from such long-term data allowing identification of knowledge gaps and data col are baselines for comparison with predicted values, and lection. There are direct and indirect effects from the intro the noise level provides information to estimate uncertain duction of transgenic plants into an environment. Direct ties of the system and its perturbations. effects are predictable by well-conducted risk assessment A "marker" is critical for quantitative assessment of re studies. Indirect effects, which are less predictable than combinant DNA (recDNA) released into the environment. direct effects, occur on nontargeted organisms feeding on A good marker is sensitive, specific, efficient, and low cost. the targeted organisms. For example, many lepidopteran Several major techniques exist for DNA marker develop (butterfly and moth) species were destroyed by parasites ment: genetic-engineering, radioactivity, fluorescence, and imported into Hawaii for moth control, causing the ex immunology. Currently, antibiotic resistance is the primary tinction of several important predators including wasps marker for quantitative monitoring of GEM populations and insect-eating birds (Howarth 1980). Similarly, using (Kluepfel et al. 1991). Markers of this type generally affect fungi to control weeds can adversely affect animals that the competitive ability of an organism and therefore, are depend on the weeds. Fuxa (1988) estimated that about 8 less useful for monitoring programs that are aimed at sur percent of introductions for biological control, including vival prediction. In the transgenic poplar, a chlorampheni insects and fungi, have caused extinction of native spe col acetyltransferase (CA1) gene is used as reporter and cies. Sometimes, the physical environment could also be marker gene (McNabb et al. 1991). When detected by a affected by introduced organisms. For example, large-scale DNA probe, specific sequences of genetic code provide a application of non-ice-nucleating bacteria could alter nor sensitive marker, but associated cost and time limitations mal precipitation patterns. Gene flow of an introduced may restrict quantitative analysis. transgene into nontransgenic populations is also a major The "endpoint" is a value used to characterize change concern because it could result in unwanted evolutionary at a particular level of interest (Suter 1990). Any change in consequences within an ecosystem (McPartlan and Dale an ecosystem arises from changes at the individual, popu 1994; Morris et al. 1994, 1994; Sawahel1994). Assessing in lation, community, or ecosystem level. To assess impact direct effects from ecological and evolutionary consequences efficiently, an endpoint is defined to determine assessment on the ecosystem is, however, difficult (Williamson 1993). output clearly. Suter (1990) proposed 2 types of endpoints In plant pathology, 2 types of potential risk occur. If ge in environmental risk assessment: 1) "assessment end netically modified crops are introduced, there is a risk that point," which is a formal expression of the actual environ low durability resistance (Miller 1993; Rogers and Parkes mental values to be protected; and 2) "measurement 1995) or a change in pathogens, such as plant virus alter endpoint," which is an expression of an observed or mea ation will be introduced (Zoeten 1991). If modified mi sured response to the hazard. Suter suggested that all risk crobes are introduced, there is a risk that they could assessments must have assessment endpoints based on become a new pathogen. Methods to identify this type of assumptions; however, a measurement endpoint is notal risk are available and commonly involve host-range test ways possible because it must be based on observations. ing of microbes before experimental release. Currently, to Suter (1990) proposed that a good assessment endpoint determine host range a close phylogenetic relationship be should be: 1) socially and biologically relevant; 2) have tween plants and their coevolved pathogens is assumed. clear a operational definition, measurability and accessi- For example, recombinant ice-nucleating bacteria were

266 USDA Forest Service Gen. Tech. Rep. RM-GTR-297. 1997. Biotechnology Risk Assessment: A View From Plant Pathology

tested on 75 plant species for pathogenicity and survival. Information Collection and Generation Often, assessment results vary with the testing scale. Two pathogen-based biological control studies used the same Data and information from previous research have been fungus, Colletotrichum gloeosporioides f. sp. aeschynomene used in almost every study on impact assessment. (TeBeest 1988; Weidemann and TeBeest 1990), but a dif MacKenzie and Henry (1991) stated, in the National Bio ferent number of species to determine the host range. In logical Impact Assessment Program (NBIAP), that analy these studies, the potential number of hosts increased sis of existing knowledge would identify information gaps as the number of tested species increased. Host range and determine the biosafety research needed. Before it is testing is helpful to avoid nontarget effects; however, analyzed, data cannot provide the basis for a decision. Hollander (1991) considered that a pathogen's host Published results appropriately interpreted are considered range can change to permit exploitation of new food information and are acceptable for use in decision-mak sources. For example, about 30 percent of pathogens ing. However, because information can be misleading, attacking U.S. crops, originally fed on native vegeta knowledge should be considered an abstraction of vali tion before evolution allowed feeding on crop plants. dated information. Knowledge is useful for reliable assess While much has been learned about pathogen-host co ment, but assumptions are often required when knowledge evolution, our ability to predict potential genetic vari is unavailable. ability of many pathogens remains limited (Weidemann Because of the perceived or unknown nature of an in and TeBeest 1990). troduced organism, genetically engineered organisms are Information is lacking on the general risks of transgenic tested in microcosms to collect data for a risk assessment woody plants because data on the environmental impacts project. A preliminary step is to use a microcosm analo of genetically modified, perennial crops, which are allowed gous to field conditions for collecting data in the labora to undergo reproductive processes in the field, is limited. tory. A microcosm is a powerful tool for collecting primary Because woody plants are part of natural forests, their risk data under· relatively realistic, albeit restricted, conditions, management is less controllable than annual/biannual which allows diverse plant pathogens to be safely and ef crop systems. Studies are needed to directly address the ficiently studied. environmental impacts of transgenic woody plants. Be In plant pathology, microcosms are used to test an cause of diversity in forest ecosystems, risk assessment of organism's response to specific environmental factors, transgenic forestry crops is distinct from that of agronomic which allows quantitative extrapolation of research results crops. Forest trees have undergone relatively little domes to the field environment for model development. There tication and often have re~ated wild relatives growing in are 2 types of microcosms: 1) a simple design such as a the same area, which increases the likelihood of hybrid growth chamber, which answers a few specific questions; ization between introduced and native trees. For example, and 2) a subunit of a natural system that contains selected some researchers used genetic engineering to improve sensitive abiotic and biotic components (Fournie et al. 1988; herbicide resistance of woody plants (Brasileiro et al. 1992; Pritchard et al. 1988). Data collection from a microcosm De Block 1990; Devillard 1992; Fillatti et al. 1987). Hybrid depends on the specific endpoint(s) of an assessment. For ization between transgenic and wild plants can produce a transgenic herbicide-resistant soybeans, many tests can be means of escape for engineered herbicide-resistance genes. conducted within a microcosm. Plant pathologists can use Klinger and Ellstrand (1994) demonstrated with Raphmws microcosms to assess the survival of microbes under vari sativus that an advantageous transgene introduced into ous simulated environments. Transgenic poplar plantlets natural populations tends to remain. Raybould and Gray were tested in a microcosm greenhouse at Iowa State Uni (1994) suggested a possible invasion of hybrids produced versity before field release (Klopfenstein et al. 1991). by crossing genetically modified crops with natural com Recent studies show that microcosm tests are useful to munities. predict outcomes of many field trials of transgenic agro Risk associated with transgenic trees involves the fol nomic crops or microbes. Lindow and Panopoulos (1988) lowing questions: 1) Would the engineered gene be trans compared survival of non-ice-nucleating Pseudomonas mitted to other trees in the wild? 2) How does transgenic syringae in microcosms to survival in field tests and con pollen compete with wild-type pollen in the environment? cluded that microcosm results can closely predict field 3) What is the fitness of the developing progeny resulting outputs. Work by Kluepfel et al. (1991) and Cook et al. from transgenic pollen compared with that of progeny re (1991) provides additional evidence that microcosm stud sulting from wild-type pollen? 4) What is the stability and ies can predict the spread and survival of genetically engi potential spread of the transgene in wild species? and 5) neered bacteria in the field. What are the overall effects of the transgene on the eco However, no microcosm study can replace field trials. A system? Another chapter (Raffa et al.) in this volume pro field test provides data on the population dynamics of an vides a detailed analysis of determining the potential risk organism under natural conditions. After microcosm stud associated with releasing transgenic poplar. ies show that potential hazards are controllable in the field,

USDA Forest Service Gen. Tech. Rep. RM-GTR-297. 1997. 267 Section V Biotechnological Applications

field tests of introduced organisms may be needed after procedure to infer an answer, is a computer program de approval by the appropriate government agencies. In a signed to simulate the problem-solving mechanism used microcosm, simulating an entire system with all possible by subject matter experts (Latin et al. 1987). Until general environmental conditions is impossible. Only field experi knowledge on the entire impact assessment process is ments provide data that comprehensively reflect there available for field tests with GMOs, the only available sys sponse of a released organism. tem for impact assessment is the electronic bulletin board Most early field experiments examined the development used by the National Biological Impact Assessment Pro of released transgenic plants. For example, the field test of gram (MacKenzie and Henry 1991). In comparison with transgenic poplar in Iowa determined if introduction posed expert panels, expert systems are better for information an environmental risk (McNabb et al. 1991). Little infor delivery rather than improving assessment reliability. mation is available on competition between transgenic and When quantitative information is available, a model wild-type woody plants. Information on competition be provides a positive or negative answer and an assessment tween introduced and native organisms is urgently needed of risk magnitude. Empirical and me~hanistic models are for regulatory agencies associated with risk assessment. available for prediction. Empirical models use statistical Such information can only be confirmed in the field. An methods such as regression models, with limited predic engineered trait without any adaptive advantage will prob tive ability for biotechnology-related assessment. Mecha ably not persist in the population. The selective advan nistic models use an understanding of underlying tage of an engineered trait must be great enough to improve processes within an ecosystem. Most models used for risk the fitness of the transgenic plants in comparison to assessment are simulations that, when coupled with data wild-type plants. Apart from their value in the impact as bases and extrapolation algorithms, are useful to assess sessment process, data from field studies also validate re different ecosystem change strategies (Teng 1991). Simu sults from models and confirm conclusions from lation modeling, considered the most reliable technique microcosm studies. for risk assessment (Duniker and Baskerville 1986; Teng 1991 ), has been used to assess chemical risks to the envi ronment (Barnthouse and Suter 1984; O'Neill et al. 1982), Synthesizing Information impacts of plant pathogens in biocontrol (DeJont et al. 1990), plant quarantine programs (Yang et al. 1991), and Mechanisms for rationally synthesizing information are biotechnology benefits (Andow et al. 1989). A simulation essential to the assessment process (Gillett 1986). This syn model was used with historical weather data to determine thesis allows organization of data by ecological and statis risk of several diseases to wheat (Luo and Zeng 1990; Luo tical methods to reflect the behavior of the ecosystem after et al. 1995). In global warming studies, simulation models introduction of the genetically modified organism (GMO). are frequently used to assess the future impact on By re-examining old data and synthesizing results, new biodiversity under different climate scenarios. information is often derived because the entire ecosystem The CLIMEX computer program developed in Austra is being considered. Models, expert panels, and expert lia exemplifies computer techniques for generating pre systems synthesize information. Expert panels are useful dictive models. The program, which compares climates in when quantitative data is unavailable, while models are ecology, was applied to modeling microbes, arthropods, valuable when enough quantitative data exist to estimate and plants (Sutherst and Maywald 1985; Worner 1988). the parameters of an assessed system. Models also pro Concerns about global climate change, have focused at vide information about the behavior of an introduced or tention on the theory and methodology of climatic require ganism under ranging weather conditions, which expert ments of organisms as tools for predictive ecology. If panels and expert systems do not. These projections de transgenic poplar grows over large areas, the CLIMAX pend on a model's ability to reflect interactions among host, program may quantitatively assess potential damage from pathogens, and environment (Teng and Yuen 1991). new insects, pathogens, and weeds. Expert panels, groups of subject matter authorities, as sess risk. Experience with traditional unmodified organ isms provides the basis for risk analysis of genetically Prediction and Evaluation modified organisms (MacKenzie and Henry 1991). The U.S. National Biological Impact Assessment Program (NBIAP) Risk prediction uses data-based predictive models to (MacKenzie 1991) used this approach to solicit consensus estimate chances of undesirable events. Prediction can be protocols for field testing GEMs and genetically altered over time, which is assessing a future event or risk based plants. Expert opinion was used to estimate disease im on present information, or can be over space, which is re pact on crops and the potential of biotechnology to reduce gionally assessing the event or risk over a defined area impact (Herdt 1991). based on information from multiple sites. Prediction over An expert system, composed of a knowledge base and a time is feasible if baseline information is available; how-

268 USDA Forest Service Gen. Tech. Rep. RM-GTR-297. 1997. Biotechnology Risk Assessment: A View From Plant Pathology

ever, accuracy decreases as the predictions extend further risk assessment because survival and dispersal are the least into the future. known aspects of epidemiology. For example, in DeJont et Impact prediction over space and time relies on a qual al.'s (1990) assessment for a mycoherbicide, the distance ity database; prediction value is enhanced by data used in of spore dispersal was calculated by a Gaussian model with conjunction with geographic inform~tion systems (GIS) limited observations. Predictions with Gaussian models and geostatistical techniques. A database is critical for any for long-distance dispersal (greater than 1,000 m) have not regional assessment and should contain spatial data sets peen validated for many pathosystems. Furthermore, of vegetation, hosts, pathogens, weather, soil, and other socio-political factors exert a strong influence on risk in variables that represent ecosystem attributes over time. terpretation for decision making. As recommended by the Data on each variable is a descriptive information layer Gaussian model, it was decided that the safe distance be covering the region of interest. Because most ecosystem tween an applied area and an orchard was 5,000 m. How variables are interrelated, the population magnitude can ever, the Dutch government determined that the risk of be calculated if such relationships are available. Several using Chondrostereum purpureum to control Prunus serotina computerized databases are being developed for impact is acceptable when an application area is less than 500 m assessment in plant pathology. from an area of commercial fruit production (DeJont et al. Geographic information systems, computer programs 1990). This illustrates that risk assessment is distinct from that use specific mathematical algorithms to enable input, interpretation. management, analysis, and display of geographic point data (Berry 1987), are powerful tools for environmental risk assessment. A quantitative regional assessment re quires analyses of extensive spatial data. In a GIS, each data set is a layer over a geographic area; layers are physi Conclusion cally and biologically correlated. Knowing the relation ships among layers allows assessment of regional impact. A regional impact map can be composed from spatially Hundreds of field tests with GMOs have been com interrelated maps of individual layers. Because maps are pleted; the results demonstrate that. behaviors of GMOs visual evidence, they frequently help managers assess are predictable (Casper and Landsmann 1992; MacKenzie impacts and expedite the decision-making process. and Henry 1991). Currently, no generally acknowledged GISs have been used in biological impact assessment in methodology for biological impact assessment exists; most plant pathology. To predic.t the occurrence of potato-late research efforts use their own techniques. As discussed blight in Pennsylvania, Royer et al. (1990) used a disease previously, biological risk assessment includes risk deter model with inputs from a relative moisture and tempera mination and risk estimation. Risk determination results ture map. Royer and Yang (1991) used similar methods to in evaluation options, but often is the main assessment generate a potential epidemic map of soybean rust in Penn activity. This activity consists of system definition, risk sylvania and Maryland. GIS techniques allow generation identification, and determination of endpoints and knowl of hazard maps in different forms depending on data set edge gaps. Risk estimation generate's data and informa availability. However, if data are available from only lim tion from microcosm and field studies, and synthesizes ited locations, extrapolation across these locations may ecosystem-w~de information into a prediction system ca produce an overlay map that generates inaccurate conclu pable of generating options. Results from risk determina sions (Berry 1987). An impact map with distinct symbols tion and risk estimation are subject to risk evaluation. is appropriate when location number is limited. Using data from remote sensing for GIS analysis, Steven et al. (1991) predicted the potential invasion of a weed, Dyers woad (lsatis tinctoria), iri northern Utah. Although tools exist to project system behavior into the Literature Cited future, risk evaluation is still an art (Gillett 1986). Because risk is the probability of the magnitude of a hazard (Duniker and Baskerville 1986), some assessment uncer Alexander, M. 1985. Ecological consequence: reducing the tainty and subjectivity will always exist. Risk management uncertainties. Issues Sci. Techno!. 1: 57-68. depends on the extent that uncertain elements in an as Andow, D.A.; Teng, P.S.; Johnson, K.B.; Snapp, S.S. 1989. sessment have been identified. In microbe-related risk as Simulating the effects of bioengineered non-ice nucle sessment, uncertainty can arise from every ecological ating bacteria on potato yields. Agric. Systems. 29: 81- process and failure becomes a function of these events 92. (Alexander 1985). Prediction of survival and spatial dis Bamthouse, L.W.; Suter, G.W., II. 1984. Risk assessment persal produces the most uncertainty in microbe-related ecology. Mechanical Engineering. 106: 36-39.

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Ecological Applications. 1: 117-120. rhizogenes et regeneration de plantes tolerantes au basta. Klopfenstein, N.B.; Shi, N.Q.; Kernan, A.; McNabb, H.S., C. R. Acad. Sci. Paris, t. 314, Serie III: 291-298. Jr.; Hall, R.B.; Hart, E.R.; Thornburg, R.W. 1991. Duchesne, L.C. 1993. Impact of biotechnology on forest Transgenic Populus hybrid expresses a wound-induc ecosystems. The Forestry Chronicle. 3: 307-313. ible potato proteinase inhibitor II - CAT gene fusion. Duniker, P.N. 1989. Ecological effects monitoring in envi Canadian Journal of Forest Research. 21: 1321-1328. ronmental impact assessment: what can it accomplish? Klopfenstein, N.B.; McNabb, H.S., Jr.; Hart, E.R.; Hall, R.B.; J. of Environ. Management. 13: 797-805. Hanna, R.D.; Heuchelin, S.A.; Allen, K.K.; Shi, N.-Q.; Duniker, P.N.; Baskerville, G.L. 1986. A systematic ap Thronburg, R.W. 1993. Transformation of Populus hy proach to forecasting in environmental impact assess brids to study and improve pest resistance. 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