Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T12:48:14.608Z Has data issue: false hasContentIssue false
  • English
  • Français

Representative taxa in field trials for environmental risk assessment of genetically modified maize

Published online by Cambridge University Press:  30 August 2013

R. Albajes ,
B. Lumbierres ,
X. Pons  and
J. Comas
R. Albajes*
Affiliation:
Universitat de Lleida, AGROTECNIO Center, Rovira Roure 191, 25198 Lleida, Spain
B. Lumbierres
Affiliation:
Universitat de Lleida, AGROTECNIO Center, Rovira Roure 191, 25198 Lleida, Spain
X. Pons
Affiliation:
Universitat de Lleida, AGROTECNIO Center, Rovira Roure 191, 25198 Lleida, Spain
J. Comas
Affiliation:
Universitat Politècnica de Catalunya, Departament d'Enginyeria Agroalimentària i Biotecnologia, Esteve Terrades, 8, 08860 Castelldefels, Barcelona, Spain
*
*Author for correspondence Phone: +0034973702571 Fax: +0034973238301 E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

When assessing the benefits and risks of transgenic crops, one consideration is their relative effects on non-target arthropod (NTA) abundance and functions within agroecosystems. Several laboratory and field trials have been conducted in Spain since the late 1990s to assess this issue. A consideration in the design of field trials is whether it is necessary to sample most NTAs living in the crop or only representative taxa that perform main ecological functions and have a good capacity to detect small changes in their abundance. Small changes in the field abundance of an effective representative taxon should be detectable using standard experimental protocols. The ability of a species to reveal differences across treatments may be analysed by examining the detectable treatment effects for surveyed non-target organisms. Analysis of data from several NTAs recorded in 14 field trials conducted over 10 years using complete block designs allowed us to select a number of representative taxa capable of detecting changes in the density or activity of arthropod herbivores, predators, parasitoids and decomposers in transgenic and non-transgenic maize varieties. The most suitable NTA as representative taxa (with detectable treatment effects below 50%) included leafhoppers among arthropod herbivores, Orius spp., Araneae, and Carabidae among predators, chalcidids, particularly the family Mymaridae, among parasitoids and Chloropidae as decomposer. Details of sampling techniques for each sampled taxa and their advantages and disadvantages are discussed. It is concluded that abundance of taxa is the most influential factor determining their capacity to detect changes caused by genetically modified varieties.

Keywords

representative taxadetectable treatment effectGM cropsOriusAraneaeCarabidaeleafhoppers
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 103 , Issue 6 , December 2013 , pp. 724 - 733
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Albajes, R., López, C. & Pons, X. (2003) Predatory fauna in corn fields and response to imidacloprid seed treatment. Journal of Economic Entomology 96, 1805–1813.Google Scholar
Albajes, R., Lumbierres, B. & Pons, X. (2009) Responsiveness of arthropod herbivores and their natural enemies to modified weed management in corn. Environmental Entomology 38, 944–954.CrossRefGoogle ScholarPubMed
Albajes, R., Lumbierres, B. & Pons, X. (2011) Two heteropteran predators in relation to weed management in herbicide-tolerant corn. Biological Control 59, 30–36.Google Scholar
Albajes, R., Farinós, G.P., Pérez-Hedo, M., Poza de la, M., Lumbierres, B., Ortego, F., Pons, X. & Castañera, P. (2012) Post-market environmental monitoring of Bt maize in Spain: non-target effects of varieties derived from the event MON810 on predatory fauna. Spanish Journal of Agricultural Research 10, 977–985.Google Scholar
Asín, L. & Pons, X. (1998) Role of predators in maize aphid populations. pp. 505–511in Nieto Nafria, J.M. & Dixon, A.F.G. (Eds) Aphids in Natural and Managed Ecosystems. León, Spain, Universidad de León (Secretariado de Publicaciones).Google Scholar
Bilden, T., Axelsen, J.A. & Toft, S. (2000) The value of Collembola from agricultural soils as food for a generalist predator. Journal of Applied Ecology 37, 672–683.CrossRefGoogle Scholar
Brooks, D.R., Bohan, D.A., Champion, G.T. & 30 others (2003) Invertebrate responses to the management of genetically modified herbicide-tolerant and conventional spring crops. I. Soil-surface-active invertebrates. Philosophical Transactions of the Royal Society B: Biological Sciences 358, 1847–1862.Google Scholar
Carmona, D.M. & Landis, D.A. (1999) Influence of refuge habitats and cover crops on seasonal activity-density of ground beetles (Coleoptera: Carabidae) in field crops. Environmental Entomology 28, 1145–1153.Google Scholar
Duan, J.J., Jiang, C., Head, G.P., Bhatti, M.A., Ward, D.P., Levine, S.L., Nickson, T.E. & Nemeth, M.A. (2006) Statistical power analysis of a two-year field study and design of experiments to evaluate non-target effects of genetically modified Bacillus thuringiensis corn. Ecological Entomology 31, 521–531.Google Scholar
EFSA (2010) Scientific opinion on Statistical considerations for the safety evaluation of GMOs. EFSA Panel on Genetically Modified Organisms (GMO). EFSA Journal 8, 1250.Google Scholar
Gauld, I. & Bolton, B. (1988) Hymenoptera. British, Oxford, UK, Museum (Natural History) – Oxford University Press.Google Scholar
Holland, J.M. (2002) Carabid beetles: their ecology, survival and use in agroecosystems. pp. 1–40in Holland, J.M. (Ed.) The Agroecology of Carabid Beetles. Andover, UK, Intercept Ltd.Google Scholar
James, C. (2012) Global Status of Commercialized Biotech/GM Crops: 2012. ISAAA Brief No. 44. Ithaca, NY, ISAAA.Google Scholar
Kotze, D.J., Brandmayr, P., Casale, A. & 18 others (2011) Forty years of carabid beetle research in Europe-from taxonomy, biology, ecology, and population studies to bioindication, habitat assessment and conservation. ZooKeys 100, 55–148.Google Scholar
Le Quesne, W.J. & Payne, K.R. (1981) Cicadellidae (Typhlocybinae) with a Check List of the British Auchenorrhyncha (Hemiptera, Homoptera). Handbooks for the Identification of British Insects, vol. II, Part 2(c). London, UK, Royal Entomological Society of London.Google Scholar
Lewis, T. (1973) Thrips, their Biology, Ecology and Economic Importance. London, UK, Academic Press.Google Scholar
Lopez, M.D., Prasifka, J.R., Bruck, D.J. & Lewis, L.C. (2005) Utility of ground beetle species in field tests of potential non-target effects of Bt crops. Environmental Entomology 34(5), 1317–1324.Google Scholar
Ludy, C. & Lang, A. (2006) Bt maize pollen exposure and impact on the garden spider, Araneus diadematus. Entomologia Experimentalis et Applicata 118, 145–156.Google Scholar
Luff, M.L. (2007) The Carabidae (ground beetles) of Britain and Ireland. Handbooks for the Identification of British Insects, vol. 4, Part 2, 2nd edn. St Albans, UK, Royal Entomological Society.Google Scholar
Lundgren, J.G., Gassmann, A.J., Bernal, J., Duan, J.J. & Ruberson, J. (2009) Ecological compatibility of GM crops and biological control. Crop Protection 28, 1017–1030.CrossRefGoogle Scholar
Marvier, M.C., McCreedy, C., Regetz, J. & Kareiva, P. (2007) A meta-analysis of effects of Bt cotton and maize on nontarget invertebrates. Science 316, 1475–1477.CrossRefGoogle ScholarPubMed
Meissle, M. & Lang, A. (2005) Comparing methods to evaluate the effects of Bt maize and insecticide on spider assemblages. Agriculture, Ecosystems and Environment 107, 359–370.Google Scholar
Meissle, M. & Romeis, J. (2009) The web-building spider Theridion impressum (Araneae: Theridiidae) is not adversely affected by Bt maize resistant to corn rootworms. Plant Biotechnology Journal 7, 645–656.Google Scholar
Naranjo, S.E. (2005) Long-term assessment of the effects of transgenic Bt cotton on the abundance of nontarget arthropod natural enemies. Environmental Entomology 34, 1193–1210.Google Scholar
Ortego, F., Pons, X., Albajes, R. & Castañera, P. (2009) European commercial genetically modified plantings and field trials. pp. 327–343in Ferry, N. & Gatehouse, A.M.R. (Eds) Environmental Impact of Genetically Modified Crops. Wallingford, UK, CAB International.Google Scholar
Perry, J.N., Rothery, P., Clark, S.J., Heard, M.S. & Hawes, C. (2003) Design, analysis and statistical power of the Farm-Scale Evaluations of the modified herbicide-tolerant crops. Journal of Applied Ecology 40, 17–31.CrossRefGoogle Scholar
Peterson, J.A., Romero, S.A. & Harwood, J.D. (2010) Pollen interception by linyphiid spiders in a corn agroecosystem: implications for dietary diversification and risk assessment. Arthropod-plant Interactions 4, 207–217.Google Scholar
Peterson, J.A., Lundgren, J.G. & Harwood, J.D. (2011) Interactions of transgenic Bacillus thuringiensis insecticidal crops with spiders (Araneae). Journal of Arachnology 39, 1–21.CrossRefGoogle Scholar
Pons, X., Lumbierres, B., López, C. & Albajes, R. (2005) Abundance of non-target pests in transgenic Bt-maize: a farm scale study. European Journal of Entomology 102, 73–79.CrossRefGoogle Scholar
Poza de la, M., Pons, X., Farinós, G.P., López, C., Ortego, F., Eizaguirre, M., Castañera, P. & Albajes, R. (2005) Impact of farm-scale Bt maize on abundance of predatory arthropods in Spain. Crop Protection 24, 677–684.Google Scholar
Prasifka, J.R., Lopez, M.D., Hellmich, R.L., Lewis, L.C. & Dively, G.P. (2007) Comparison of pitfall traps and litter bags for sampling ground-dwelling arthropods. Journal of Economic Entomology 131, 115–120.Google Scholar
Prasifka, J.R., Hellmich, R.L., Dively, G.P., Higins, S., Dixon, P.S. & Duan, J.J. (2008) Selection of non-target arthropod taxa for field research on transgenic insecticidal crops: using empirical data and statistical power. Environmental Entomology 37, 1–10.Google Scholar
R Development Core Team (2008) R: A Language and Environment for Statistical Computing. Vienna, Austria, R Foundation for Statistical Computing.Google Scholar
Rauschen, S., Eckert, J., Frank Schaarschmidt, F., Schuphan, I. & Gathmann, A. (2008) An evaluation of methods for assessing the impacts of Bt-maize MON810 cultivation and pyrethroid insecticide use on Auchenorrhyncha (planthoppers and leafhoppers). Agricultural and Forest Entomology 10, 331–339.Google Scholar
Riechert, S.E. (1999) The hows and whys of successful pest suppression by spiders: insights from case studies. Journal of Arachnology 27, 387–396.Google Scholar
Romeis, J., Bartch, D., Bigler, F. & 16 others. (2008) Assessment of risk of insect-resistant transgenic crops to nontarget arthropods. Nature Biotechnology 26, 203–208.Google Scholar
Shelton, A.M., Naranjo, S.E., Romeis, J. & 14 others (2009) Appropriate analytical methods are necessary to assess nontarget effects of insecticidal proteins in GM crops through meta-analysis (Response to Andow et al. 200). Environmental Entomology 38, 1533–1538.Google Scholar
Sotherton, N.W. (1985) The distribution and abundance of predatory arthropods in field boundaries. Annals of Applied Biology 106, 17–21.Google Scholar
Storkey, J., Bohan, D.A., Haughton, A.J., Champion, G.T., Perry, J.N., Poppy, G.M. & Woiwood, I.P. (2008) Providing the evidence base for environmental risk assessments of novel farm management practices. Environmental Science & Policy 11, 579–587.Google Scholar
Sunderland, K. & Samu, F. (2000) Effects of agricultural diversification on the abundance, distribution, and pest control potential of spiders: a review. Entomologia Experimentalis et Applicata 95, 1–13.Google Scholar
Toft, S. & Bilde, T. (2002) Carabid diets and food value. pp. 81–110in Holland, J.M. (Ed.) The Agroecology of Carabid Beetles. Andover, UK, Intercept Ltd.Google Scholar
Wolfenbarger, L.L., Naranjo, S.E., Lundgren, J.G., Bitzer, R.J. & Watrud, L.S. (2008) Bt crop effects on functional guilds of non-target arthropods: a meta-analysis. PLoS ONE 3, e2118.Google Scholar