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Meteorological input data requirements to predict cross-pollination of GMO Maize with Lagrangian approaches

Published online by Cambridge University Press:  17 March 2007

Kai Lipsius
Affiliation:
Institute for Geoecology, Environmental Systems Analysis Group, Technical University Braunschweig, Germany
Ralf Wilhelm
Affiliation:
Federal Biological Research Center for Agriculture and Forestry (BBA), Institute for Plant Virology, Microbiology and Biosafety, Germany
Otto Richter
Affiliation:
Institute for Geoecology, Environmental Systems Analysis Group, Technical University Braunschweig, Germany
Klaus Jürgen Schmalstieg
Affiliation:
Institute for Geoecology, Environmental Systems Analysis Group, Technical University Braunschweig, Germany
Joachim Schiemann
Affiliation:
Federal Biological Research Center for Agriculture and Forestry (BBA), Institute for Plant Virology, Microbiology and Biosafety, Germany

Abstract

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Modeling pollen dispersal to predict cross-pollination is of great importance for the ongoing discussion of adventitious presence of genetically modified material in food and feed. Two different modeling approaches for pollen dispersal were used to simulate two years of data for the rate of cross-pollination of non-GM maize (Zea mays (L.)) fields by pollen from a central 1 ha transgenic field. The models combine the processes of wind pollen dispersal (transport) and pollen competition. Both models used for the simulation of pollen dispersal were Lagrangian approaches: a stochastic particle Lagrange model and a Lagrangian transfer function model. Both modeling approaches proved to be appropriate for the simulation of the cross-pollination rates. However, model performance differed significantly between years. We considered different complexity in meteorological input data. Predictions compare well with experimental results for all simplification steps, except that systematic deviations occurred when only main wind direction was used. Concluding, it can be pointed out that both models might be adapted to other pollen dispersal experiments of different crops and plot sizes, when wind direction statistics are available. However, calibration of certain model parameters is necessary.

Type
Research Article
Copyright
© ISBR, EDP Sciences, 2007

References

Angevin F, Klein E, Choimet C, Meynard J, de Rouw A, Sohbi Y (2001) Modélisation des effets des systèmes de culture et du climat sur les pollinisations croisées chez le maïs. INRAFNSEA, pp 21–36, http://www.fnsea.fr/dossiers/ogm/OGM020211e.pdf
Arritt R, Westgate M, Clark C, Fonseca A, Riese J (2003) Development of an adventitious pollen risk assessment model. In Boelt B, ed, 1st European Conference on the Coexistence of Genetically Modified Crops with Conventional and Organic Crops, Research Centre Flakkebjerg, pp 203-205
Aylor, DE, Flesch, TK (2001) Estimating spore release rates using a Lagrangian stochastic simulation model. J. Appl. Meteorol. 40: 11961208 2.0.CO;2>CrossRef
Aylor, D, Schultes, N, Shields, E (2003) An aerobiological framework for assessing crosspollination in maize. Agric. For. Meteorol. 119: 111129 CrossRef
Bock A-K, Lheureux K, Libeau-Dulos M, Nilsagard H, Rodriguez-Cerezo E (2002) Scenarios for co-existence of genetically modified, conventional and organic crops in European agriculture. IPTS-JRC, ftp://ftp.jrc.es/pub/EURdoc/eur20394en.pdf
Devaux, C, Lavigne, C, Falentin-Guyomarc'h, H, Vautrin, S, Lecomte, J, Klein, E (2005) High diversity of oilseed rape pollen clouds over an agro-ecosystem indicates long-distance dispersal. Mol. Ecol. 14: 22692280 CrossRef
Devos, Y, Reheul, D, De Schrijver A (2005) The co-existence between transgenic and nontransgenic maize in the European Union: a focus on pollen flow and cross-fertilization. Environ. Biosafety Res. 4: 71-87 CrossRef
Eastham K, Sweet J (2002) Genetically modified organisms (GMOs): the significance of gene flow through pollen transfer. EEA, http://reports.eea.eu.int/environmental_issue_report_2002_28/en/GMOs%20for%20www.pdf
EU (2003) Regulation (EC) No 1830/2003 of the European Parliament and of the Council of 22 September 2003 concerning the traceability and labelling of genetically modified organisms and the traceability of food and feed products produced from genetically modified organisms and amending Directive 2001/18/EC. http://europa.eu.int/eurlex/pri/en/oj/dat/2003/1_268/1_26820031018en00240028.pdf
Henry C, Morgan D, Weekes R, Daniels R, Boffey C (2003) Farm scale evaluations of GM crops: monitoring gene flow from GM crops to non-GM equivalent crops in the vicinity: part I: forage maize. DEFRA, http://www.defra.gov.uk/environment/gm/research/pdf/epg_1-5-138.pdf
Ireland DS, Westgate ME, Ashton BA (2001) Combining ISCST3 and AERMOD particulate dispersion models to quantify maize pollen distribution. ASACSSA-SSSA Annual Meetings, Charlotte, NC, October 21–25
Jarosz N, Loubet B, Durand B, McCartney A, Foueillassar X, Huber L (2003) Field measurements of airborne concentration and deposition rate of maize pollen. Agric. For. Meteorol. 119: 37–51
Jarosz N, Loubet B, Huber L (2004) Modelling airborne concentration and deposition rate of maize pollen. Atmos. Environ. 38: 5555–5566
Jarosz, N, Loubet, B, Durand, B, Foueillassar, X, Huber L (2005) Variations in maize pollen emission and deposition in relation to microclimate. Environ. Sci. Technol. 39: 4377-4384 CrossRef
Klein, E, Lavigne, C, Foueillassar, X, Gouyon, P-H, Larédo, C (2003) Corn pollen dispersal: quasi-mechanistic models and field experiments. Ecol. Monogr. 73: 131150 CrossRef
Klein, E, Lavigne, C, Picault, H, Renard, M, Gouyon, P-H (2006) Pollen dispersal of oilseed rape: estimation of the dispersal function and effects of field dimension. J. Appl. Ecology 43: 141-151 CrossRef
Lavigne, C, Klein, EK, Vallée, P, Pierre, J, Godelle, B, Renard, M (1998) A pollen-dispersal experiment with transgenic oilseed rape. Estimation of the average pollen dispersal of an individual plant within a field. Theor. Appl. Genet. 96: 886896 CrossRef
Loos C, Seppelt R, Meier-Bethke S, Schiemann J, Richter O (2003) Spatially explicit modelling of transgenic maize pollen dispersal and cross-pollination. J. Theor. Biol. 225: 241-255
Luna, VS, Figueroa, MJ, Baltazar, MB, Gomez, LR, Townsend, R, Schoper, JB (2001) Maize pollen longevity and distance isolation requirements for effective pollen control. Crop Sci. 41: 1551-1557 CrossRef
Ma, BL, Subedi, KD, Reid, LM (2004) Extent of cross-fertilization in maize by pollen from neighboring transgenic hybrids. Crop Sci. 44: 1273-1282 CrossRef
Meier-Bethke S, Schiemann J (2003) Effect of varying distances and intervening maize fields on outcrossing rates of transgenic maize. In Boelt B, ed, 1st European Conference on the Coexistence of Genetically Modified Crops with Conventional and Organic Crops, Research Center Flakkebjerg, pp 77–78
Nathan, R, Perry, G, Cronin, JT, Strand, AE, Cain, ML (2003) Methods for estimating long distance dispersal. Oikos 103: 261-273 CrossRef
Raynor, GS, Ogden, EC, Hayes, JV (1972) Dispersion and deposition of corn pollen from experimental sources. Agron. J. 64: 420-427 CrossRef
Seinfeld JH (1986) Atmospheric Chemistry and Physics of Air Pollution. Wiley, New York, ISBN: 0-471-82857-2, pp 880-949
Tolstrup K, Andersen S, Boelt B, Buus M, Gylling M, Holm P, Kjellson G, Pedersen S, Oestergard H, Mikkelsen SA (2003) Report from the working group on the co-existence of genetically modified crop with conventional and organic crops. DIAS, http://web.agrsci.dk/gmcc-03/Co_exist_rapport.pdf
Treu R, Emberlin J (2000) Pollen dispersal in the crops maize (Zea mays), oilseed rape (Brassica napus ssp. oleifera), potatoes (Solanum tuberosum), sugar beet (Beta vulgaris ssp. vulgaris) and wheat (Triticum aestivum). Soil Association, http://www.soilassociation.org/web/sa/saweb.nsf/librarytitles/GMO14012000/$file/Pollen%20Dispersal%20Report.pdf
Tufto, J, Engen, S, Hindar, K (1997) Stochastic dispersal processes in plant populations. Theor. Pop. Biol. 52: 1626. CrossRef
VDI (2000) Environmental meteorology, Atmospheric dispersion models: Particle model. VDI Richtlinien, VDI 3945, Beuth Verlag, Berlin
Weber, W, Bringezu, T, Broer, I, Holz, F, Eder, J (2005) Koexistenz von gentechnisch verändertem und konventionellem Mais. Mais 1: 16
Yamamura, K (2004) Dispersal distance of corn pollen under fluctuating diffusion coefficient. Popul. Ecol. 46: 87-101 CrossRef