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How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape?

Identifieur interne : 000303 ( PascalFrancis/Corpus ); précédent : 000302; suivant : 000304

How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape?

Auteurs : Claire Lavigne ; Etienne K. Klein ; Jean-Francois Mari ; Florence Le Ber ; Katarzyna Adamczyk ; Hervé Monod ; Frédérique Angevin

Source :

RBID : Pascal:08-0361464

Descripteurs français

English descriptors

Abstract

1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 × 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

pA  
A01 01  1    @0 0021-8901
A02 01      @0 JAPEAI
A03   1    @0 J. appl. ecol.
A05       @2 45
A06       @2 4
A08 01  1  ENG  @1 How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape?
A11 01  1    @1 LAVIGNE (Claire)
A11 02  1    @1 KLEIN (Etienne K.)
A11 03  1    @1 MARI (Jean-Francois)
A11 04  1    @1 LE BER (Florence)
A11 05  1    @1 ADAMCZYK (Katarzyna)
A11 06  1    @1 MONOD (Hervé)
A11 07  1    @1 ANGEVIN (Frédérique)
A14 01      @1 INRA, UR 1115 Plantes et Systèmes de culture Horticoles @2 84000 Avignon @3 FRA @Z 1 aut.
A14 02      @1 INRA, UR 546 Biostatistique et Processus Spatiaux @2 84000 Avignon @3 FRA @Z 2 aut.
A14 03      @1 Université Nancy 2, UMR 7503 LORIA @2 54500 Vandoeuvre-Lès-Nancy @3 FRA @Z 3 aut.
A14 04      @1 ENGEES, UMR MAI 101 CEVH @2 67000 Strasbourg @3 FRA @Z 4 aut.
A14 05      @1 INRA, UR 341 Mathématiques et Informatique Appliquées @2 78352 Jouy-en-Josas @3 FRA @Z 5 aut. @Z 6 aut.
A14 06      @1 INRA, UAR 1240 Eco-Innov @2 78850 Thiverval Grignon @3 FRA @Z 7 aut.
A20       @1 1104-1113
A21       @1 2008
A23 01      @0 ENG
A43 01      @1 INIST @2 11538 @5 354000197666750120
A44       @0 0000 @1 © 2008 INIST-CNRS. All rights reserved.
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A47 01  1    @0 08-0361464
A60       @1 P
A61       @0 A
A64 01  1    @0 Journal of applied ecology
A66 01      @0 GBR
C01 01    ENG  @0 1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 × 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal.
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C02 02  X    @0 002A31D07E
C02 03  X    @0 215
C03 01  X  FRE  @0 Organisme génétiquement modifié @5 01
C03 01  X  ENG  @0 Genetically modified organism @5 01
C03 01  X  SPA  @0 Organismo modificado genéticamente @5 01
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C03 02  X  SPA  @0 Polen @5 02
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C03 03  X  ENG  @0 Rural environment @5 03
C03 03  X  SPA  @0 Medio rural @5 03
C03 04  X  FRE  @0 Coexistence @5 04
C03 04  X  ENG  @0 Coexistence @5 04
C03 04  X  SPA  @0 Coexistencia @5 04
C03 05  X  FRE  @0 Maïs @5 05
C03 05  X  ENG  @0 Corn @5 05
C03 05  X  SPA  @0 Maiz @5 05
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C03 06  X  ENG  @0 Allogamy @5 06
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C03 08  X  SPA  @0 Dispersión @5 08
C03 09  X  FRE  @0 Répartition spatiale @5 09
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C03 09  X  SPA  @0 Distribución espacial @5 09
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C03 10  X  ENG  @0 Transgenic plant @5 49
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C03 11  X  ENG  @0 Rural landscape @4 CD @5 96
C03 11  X  SPA  @0 Paisaje rural @4 CD @5 96
C03 12  X  FRE  @0 Pollinisation croisée @4 CD @5 97
C03 12  X  ENG  @0 Cross pollination @4 CD @5 97
C03 12  X  SPA  @0 Polinizacion cruzada @4 CD @5 97
N21       @1 231
N44 01      @1 OTO
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Format Inist (serveur)

NO : PASCAL 08-0361464 INIST
ET : How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape?
AU : LAVIGNE (Claire); KLEIN (Etienne K.); MARI (Jean-Francois); LE BER (Florence); ADAMCZYK (Katarzyna); MONOD (Hervé); ANGEVIN (Frédérique)
AF : INRA, UR 1115 Plantes et Systèmes de culture Horticoles/84000 Avignon/France (1 aut.); INRA, UR 546 Biostatistique et Processus Spatiaux/84000 Avignon/France (2 aut.); Université Nancy 2, UMR 7503 LORIA/54500 Vandoeuvre-Lès-Nancy/France (3 aut.); ENGEES, UMR MAI 101 CEVH/67000 Strasbourg/France (4 aut.); INRA, UR 341 Mathématiques et Informatique Appliquées/78352 Jouy-en-Josas/France (5 aut., 6 aut.); INRA, UAR 1240 Eco-Innov/78850 Thiverval Grignon/France (7 aut.)
DT : Publication en série; Niveau analytique
SO : Journal of applied ecology; ISSN 0021-8901; Coden JAPEAI; Royaume-Uni; Da. 2008; Vol. 45; No. 4; Pp. 1104-1113; Bibl. 3/4 p.
LA : Anglais
EA : 1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 × 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal.
CC : 002A14D01; 002A31D07E; 215
FD : Organisme génétiquement modifié; Pollen; Milieu rural; Coexistence; Maïs; Allogamie; Modèle; Dispersion; Répartition spatiale; Plante transgénique; Paysage rural; Pollinisation croisée
ED : Genetically modified organism; Pollen; Rural environment; Coexistence; Corn; Allogamy; Models; Dispersion; Spatial distribution; Transgenic plant; Rural landscape; Cross pollination
SD : Organismo modificado genéticamente; Polen; Medio rural; Coexistencia; Maiz; Modelo; Dispersión; Distribución espacial; Planta transgénica; Paisaje rural; Polinizacion cruzada
LO : INIST-11538.354000197666750120
ID : 08-0361464

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Pascal:08-0361464

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<div type="abstract" xml:lang="en">1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 × 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal.</div>
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<s0>1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 × 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal.</s0>
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<s5>01</s5>
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<s5>02</s5>
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<s5>03</s5>
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<s5>03</s5>
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<s5>03</s5>
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<s5>04</s5>
</fC03>
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<s0>Coexistence</s0>
<s5>04</s5>
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<s5>04</s5>
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<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG">
<s0>Corn</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA">
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<s5>05</s5>
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<s0>Allogamie</s0>
<s5>06</s5>
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<s5>06</s5>
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<s5>09</s5>
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<s0>Plante transgénique</s0>
<s5>49</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG">
<s0>Transgenic plant</s0>
<s5>49</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA">
<s0>Planta transgénica</s0>
<s5>49</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE">
<s0>Paysage rural</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG">
<s0>Rural landscape</s0>
<s4>CD</s4>
<s5>96</s5>
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<fC03 i1="11" i2="X" l="SPA">
<s0>Paisaje rural</s0>
<s4>CD</s4>
<s5>96</s5>
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<s4>CD</s4>
<s5>97</s5>
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<s5>97</s5>
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<s0>Polinizacion cruzada</s0>
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<s5>97</s5>
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<s1>231</s1>
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<NO>PASCAL 08-0361464 INIST</NO>
<ET>How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape?</ET>
<AU>LAVIGNE (Claire); KLEIN (Etienne K.); MARI (Jean-Francois); LE BER (Florence); ADAMCZYK (Katarzyna); MONOD (Hervé); ANGEVIN (Frédérique)</AU>
<AF>INRA, UR 1115 Plantes et Systèmes de culture Horticoles/84000 Avignon/France (1 aut.); INRA, UR 546 Biostatistique et Processus Spatiaux/84000 Avignon/France (2 aut.); Université Nancy 2, UMR 7503 LORIA/54500 Vandoeuvre-Lès-Nancy/France (3 aut.); ENGEES, UMR MAI 101 CEVH/67000 Strasbourg/France (4 aut.); INRA, UR 341 Mathématiques et Informatique Appliquées/78352 Jouy-en-Josas/France (5 aut., 6 aut.); INRA, UAR 1240 Eco-Innov/78850 Thiverval Grignon/France (7 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Journal of applied ecology; ISSN 0021-8901; Coden JAPEAI; Royaume-Uni; Da. 2008; Vol. 45; No. 4; Pp. 1104-1113; Bibl. 3/4 p.</SO>
<LA>Anglais</LA>
<EA>1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 × 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal.</EA>
<CC>002A14D01; 002A31D07E; 215</CC>
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<ED>Genetically modified organism; Pollen; Rural environment; Coexistence; Corn; Allogamy; Models; Dispersion; Spatial distribution; Transgenic plant; Rural landscape; Cross pollination</ED>
<SD>Organismo modificado genéticamente; Polen; Medio rural; Coexistencia; Maiz; Modelo; Dispersión; Distribución espacial; Planta transgénica; Paisaje rural; Polinizacion cruzada</SD>
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