Co-existence with GM crops in European Agriculture

SIGMEA logoThe EU project SIGMEA is examining the feasibility of growing GM and other crops together in the agricultural landscapes of Europe. A central part of the project - Workpackage 2 or WP2 - collates and analyses experimental studies on geneflow by seed and pollen, but also considers field experiments on the ecological impacts of GM cropping. WP2 has over 20 partners who are sharing and analysing definitive data on over 100 field experiments, making the SIGMEA database the most comprehensive of its type. The agroecology group at SCRI co-ordinates this unique synthesis of biology and agronomy. Contact: Geoff Squire

Findings and outputs

SIGMEA is making science-based recommendations on how to achieve co-existence, where possible, between GM crops and other forms of cropping in the varied agricultural regions of Europe. For a summary of the conclusions of Workpackage 2 specific to GM coexistence (cross-pollination, volunteers weeds, ferals, wild relatives) mainly in maize, oilseed rape and beet:

Final reports of the whole project can be viewed at the SIGMEA project website. The following article summarises the main findings.

Latest article from the SIGMEA WP2 team on the ststus of feral oilseed rape in Europe:

Preliminary findings were presented at the GMCC-07 conference at Seville, November 2007, for which there is now an online book of abstracts. The following article in GMCC 05 at Montpellier, France gives some of the background to geneflow studies in SIGMEA.

Ecological impacts

SIGMEA WP2 has also assessed the ecological impacts of GM insect-resistant (Bt) maize and herbicide-tolerant oilseed rape. The main conclusions based on recent field studies are as follows (for details see the final report on Task 2.6.2).

  • Bt maize resistant to corn borers. Data from field trials in different parts of Europe pointed to the same conclusion that, compared to reference treatments 'Bt maize had no consistent effects on any of the invertebrates or soil organisms studied over a time period of several years. In contrast, in the same time periods, other agronomic factors did have large and measurable effects on the same organisms.' Additional research is recommended for some poorly studied invertebrate and microbial groups, but the report cautions that any effects found (positive or negative) should be weighed against the often large effects resulting from change in general agricultural practice.
  • Herbicide-tolerant oilseed rape. The broad-spectrum herbicides used with HT oilseed rape would likely cause small adverse effects (compared to current practice) on already impoverished arable food webs. In addition, the presence of GMHT volunteer weeds would make weed control more difficult and so limit the choices for growing some broadleaf crops. Beneficial effects, such as through the use of fewer or less toxic (than current) herbicides, are unlikely to outweight the negative effects. These conclusions, for GMHT oilseed rape in Europe, may not be applicable to oilseed rape in other parts of the world.
  • On GM risk assessment generally - the report concludes that with the right experimental design, the effects of GM crops can indeed be detected above the 'noise' of ecological processes; that future assessments should be more holistic, considering both positive and negative; and that much more effort is needed to set criteria for resilient, healthy systems aginst which any new biotechnology can be assessed.

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SIGMEA data-providers

Map of sites in the SIGMEA project - red, maize; blue, beet; yellow, oilseed rape

The SIGMEA database compiled by WP2, with its experiments, analysis, modelling and data-mining, is the largest collection of information of its type in Europe, probably in the world. The content, which includes more than 150 experiment-years of field data, is the basis of SIGMEA's consensus documents and crop-specific summaries. WP2 consisted of research groups in the following organisations.

Czech Republic
Czech University of Agriculture in Prague
Czech Republic
University of South Bohemia
Denmark
Riso National Laboratory
France
University of Paris 11
France
Institut National de la Recherche Agronomique / Centre Technique Interprofessionnel des Oléagineux Métropolitains
Germany
Technische Universitaet Muenchen
Germany
University of Bremen
Germany
Federal Biological Research Centre for Agriculture and Forestry
Germany
University of Hohenheim
Germany
Bundesamt für Verbraucherschutz und Lebensmittelsicherheit
Italy
Istituto Sperimentale per le Colture Industriali
Italy
Universita Politecnica delle Marche
The Netherlands
Plant Research International
Poland
Plant Breeding and Acclimatisation Institute
Spain
Institut de Recerca i Tecnologia Agroalimentàries
Spain
Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria
Spain
Consejo Superior de Investigaciones Cientificas
Switzerland
Swiss Federal Institute of Technology
UK
Institute of Grassland and Environmental Research
UK
NIAB
UK
Rothamsted Research
UK
Scottish Crop Research Institute

In addition to the above, SCRI's main contacts in SIGMEA have been principally through: Marko Debeljak and Saso Dzeroski at IJS Slovenia for data mining and decision-support; Frederique Angevin, Nathalie Colbach and colleagues at INRA France for gene flow modelling; Joe Perry and colleagues at Rothamsted Research for landscape and field patterns; Hauke Reuter and Broder Breckling at the University of Bremen for upscaling; Christophe Sausse at CETIOM France for regional case study areas; and Antoine Messean (INRA) and Jeremy Sweet (consultant) for scientific and administrative co-ordination.

Photograph of the SIGMEA group at Dundee 2006

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The origin of impurities

Impurities in crops arise through three main routes: by cross pollination between crops in flower at the same time; by plants of the same or similar type growing within a crop (commonly known as volunteers); and by impurities in the sown seed that arose through a previous event, usually when the seed company bulks a crop variety for sale to farmers. The aim of SIGMEA was to collate and analyse all known data in Europe on those processes that operate in the agricultural landscape - cross pollination and transmission by volunteers, ferals and wild relatives. The collated data are being used by other groups in SIGMEA for modelling, data-mining and testing options for co-existence. The information was assembled in the following main categories:

  • cross pollination between crops (distance, pollen fertility, landscape configurations)
  • volunteer weeds (life cycle, fitness, genetic variation, agronomic control)
  • introgression to wild relatives
  • demography of feral populations
  • ecological impacts of GM cropping
  • scaling from individual plants to agricultural landscapes 

The emphasis was on maize and oilseed rape on which most research had been done. Much information was also collated on beet, especially the role of its wild relative - sea beet. A small amount of data on wheat and rice in Europe was also included.

Background to co-existence

Whatever your view of GM crops, they are part of global agriculture. There are still very few examples of GM crops being grown commercially in Europe but potential new GM varieties are moving through the regulatory system. When GM traits have been through a thorough environmental risk-assessment, the remaining practical question in Europe is whether it is possible to grow them in the same agricultural region as other cropping systems, for example integrated, organic or commodity-driven.

It is widely accepted that impurities (GM or otherwise) will arise in crops through sown seed, cross pollination from another field and volunteer weeds in the same field. In view of this, the EU has set a labelling threshold of 0.9 per cent for the total content of such impurities. If a non-GM crop has a GM content above 0.9 per cent, it must be labelled as containing GM product. If below 0.9 per cent then it need not be labelled as such. The 0.9 per cent is not based on any particular scientific point but is low and is just about attainable with best farming practice. A threshold of 0.1 per cent, for example, would be difficult to attain in most instances. The question then is how can cropping be managed - in space and over time - so that the GM content of non-GM crops is below 0.9 per cent. (Note that non-GM crops will also bring impurities to GM crops but hardly anyone is concerned about that.)

While labelling is the main issue in co-existence, the mechanisms that have to be managed are biological and agronomic. They include cross pollination, life cycle biology (particularly seed dormancy and germination) and genetic recombination; tillage, crop rotation and weed control. There is much research on these topics but it has so far been fragmented and has not lead to any consensus about co-existence among sceintists in Europe. To remedy this, the EU project SIGMEA (a STREP funded under FP6) aims to provide the scientific basis for recommendations on co-existence. SIGMEA's activities comprise data-collation, gene flow modelling, regional case studies, a landscape generator that models field patterns over a cropping sequence, and range of other tasks that contribute to monitoring GMOs, legal aspects of co-existence and decision aids for policy and farmers.

Image of weed beet flowering in sugar beet - thanks to Katarina Novakova, Czech University of Agriculture

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Asssembling the SIGMEA database

SCRI's role in SIGMEA is to manage the construction and use of a database of experimental work in Europe, to work with partners to interrogate and interpret the database, and to summarise the conclusions of partners on GM coexistence and GM impacts. The workpackage that dealt with these activities (about half of SIGMEA) was led from SCRI by Geoff Squire. The database was managed by Mark Young. Technical work was done by Linda Ford, Gill Banks and Lawrie Brown. Others at SCRI who contributed expertise included Graham Begg (population modelling, statistics), Danny Cullen (detection, diagnostics), Cathy Hawes (food webs, trophic interactions), Pete Iannetta (persistence, ELISA), and Gavin Ramsay (pollination, genetics).

The essential feature of SIGMEA is that partners contribute full details of their experiments to a communal database. Each experiment is submitted with a base document which explains the background, methods and main results and this accompanies data sheets such as spreadsheet files and GIS layers. All submitted files are meticulously annotated by the provider and checked by reviewers within SIGMEA. A great deal of trust has been shown among the scientists involved, especially given that most of the data are not yet published. Without this trust, there would be no database and no co-operation on analysis.

The data allow comparison of processes such as gene flow across spatial scales (plots, fields, landscapes) and between different regions of Europe. So, for example, early studies on cross pollination from GM to non-GM maize measured in moderate sized plots, carried out as part of the tiered approach to GM releases, can be compared with the real thing - field-to-field measurements in commercial agriculture. The effect of local environments on, say, cross pollination in maize can be assessed by comparing experimental data from Spain, Germany, the UK and Switzerland. New modelling and data-mining methods are being tested on such data.

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