A framework for a European network for a systematic environmental impact assessment of genetically modified organisms (GMO)

Abstract

The assessment of the impacts of growing genetically modified (GM) crops remains a major political and scientific challenge in Europe. Concerns have been raised by the evidence of adverse and unexpected environmental effects and differing opinions on the outcomes of environmental risk assessments (ERA). The current regulatory system is hampered by insufficiently developed methods for GM crop safety testing and introduction studies. Improvement to the regulatory system needs to address the lack of well designed GM crop monitoring frameworks, professional and financial conflicts of interest within the ERA research and testing community, weaknesses in consideration of stakeholder interests and specific regional condi- tions, and the lack of comprehensive assessments that address the environmental and socio-economic risk assessment interface. To address these challenges, we propose a European Network for systematic GMO impact assessment (ENSyGMO) with the aim directly to enhance ERA and post-market environmental monitoring (PMEM) of GM crops, to harmonize and ultimately secure the long-term socio-political impact of the ERA process and the PMEM in the EU. These goals would be achieved with a multi-dimen- sional and multi-sector approach to GM crop impact assessment, targeting the variability and complexity of the EU agro-environment and the relationship with relevant socio-economic factors. Specifically, we propose to develop and apply methodologies for both indicator and field site selection for GM crop ERA and PMEM, embedded in an EU-wide typology of agro-environments. These methodologies should be applied in a pan-European field testing network using GM crops. The design of the field experiments and the sampling methodology at these field sites should follow specific hypotheses on GM crop effects and use state-of-the art sampling, statistics and modelling approaches. To address public concerns and cre- ate confidence in the ENSyGMO results, actors with relevant specialist knowledge from various sectors should be involved.

Full text

A framework for a European network for a systematic environmental impact assessment... 73
A framework for a European network for a systematic
environmental impact assessment of genetically
modified organisms (GMO)
Frieder Graef1, 22, Jörg Römbke2, Rosa Binimelis3, Anne Ingeborg Myhr4,
Angelika Hilbeck5, Broder Breckling6, Tommy Dalgaard7, Ulrich Stachow1,
Georgina Catacora-Vargas4, omas Bøhn4, 28, David Quist4, Béla Darvas8, 29,
Gert Dudel9, Bernadette Oehen10, Hartmut Meyer11, Klaus Henle12,
Brian Wynne13, Marc J. Metzger14, Silvio Knäbe15, Josef Settele16,
András Székács8, 29, Angelika Wurbs1, Jeannette Bernard17,
Donal Murphy-Bokern18, Marcello Buiatti19, Manuela Giovannetti19,
Marko Debeljak20, Erling Andersen21, Andreas Paetz17, Saso Dzeroski20,
Beatrix Tappeser22, Cornelis A.M. van Gestel23, Werner Wosniok24,
Gilles-Eric Séralini25, Iulie Aslaksen26, 4, Roland Pesch6, Stanislav Maly27,
Armin Werner1
1 ZALF, Leibniz Centre for Agricultural Landscape Research, Institute of Land Use Systems, Eberswalder Str.
84, 15374 Müncheberg, Germany 2 ECT Oekotoxikologie GmbH; Böttgerstr. 2-14; 65439 Flörsheim a.M.,
Germany 3 Center for Agro-food Economy and Development-CREDA-UPC-IRTA; Parc Mediterrani de la
Tecnologia- ESAB Building; C/ Esteve Terrades 8; 08860 Castelldefels (Barcelona), Spain 4 GenØk; Centre
for Biosafety, Science Park, 9294 Tromsø; Norway 5 ETH; Swiss Federal Institute of Technology, Institute of
Integrative Biology, Universitaetstr. 16; 8092 Zürich; Switzerland 6 University of Vechta; Chair of Landscape
Ecology; Driverstr. 22; 49377 Vechta; Germany 7 Aarhus University; Department of Agroecology; Blichers Allé
20; 8830 Tjele; Denmark 8 Plant Protection Institute of the Hungarian Academy of Sciences; Department of
Ecotoxicology and Environmental Analysis; Herman Otto ut 15; 1022 Budapest; Hungary 9 TUD; Technische
Universität Dresden; Faculty of Geo-, Forest- and Hydroscience; Helmholtzstr. 10; 01069 Dresden; Germany
10 FiBL; Forschungsinstitut für Biologischen Landbau; Ackerstr. 1; 5070 Frick; Switzerland 11 ENSSER,
Postfach 1102, 15832 Rangsdorf, Germany 12 UFZ; Helmholtz Centre for Environmental Research; De-
partment of Conservation Biology; Permoserstr. 15; 04318 Leipzig; Germany 13 ESRC Cesagen, Lancaster
University; Sociology; Bailrigg; LA1 4YD Lancaster; UK 14 e University of Edinburgh; School of GeoScien-
ces; Drummond Street; Edinburgh EH8 9XP; UK 15 EAS; Eurons Agroscience Services GmbH; Eutinger
Strasse 24; 75223 Niefern-Öschelbronn; Germany 16 UFZ; Helmholtz Centre for Environmental Research;
Department of Community Ecology; eodor-Lieser-Str. 4; 06120 Halle; Germany 17 DIN; Deutsches In-
stitut für Normung; Burggrafenstr. 6; 10787 Berlin; Germany 18 Donal Murphy-Bokern; Lindenweg 12;
49393 Kroge-Ehrendorf; Germany 19 UDP; University of Pisa; Department of Crop Plant Biology; Via del
Borghetto 80, 56124 Pisa; Italy 20 JSI; Josef Stefan Institute; Department of Knowledge Technologies; Jamova
39; 1000 Ljubljana; Slovenia 21 University of Copenhagen; Faculty of Life Sciences; Rolighedsvej 23; 1958
Frederiksberg C; Denmark 22 BfN; Federal Agency for Nature Conservation; Division GMO-Regulation, Bio-
BioRisk 7: 73–97 (2012)
doi: 10.3897/biorisk.7.1969
www.pensoftonline.net/biorisk
Copyright Frieder Graef et al. This is an open access article distributed under the terms of the Creative Commons Attribution License 3.0
(CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RESEARCH ARTICLE
BioRisk
A peer-reviewed open-access journal

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
74
safety; Konstantinstr. 110; 53179 Bonn; Germany 23 VU University, Amsterdam; Faculty of Earth and Life
Sciences; De Boelelaan 1085; 1081 HV Amsterdam; e Netherlands 24 University of Bremen, Department
of Mathematics and Computer Science; Bibliothekstr. 1; 28359 Bremen; Germany 25 CRIIGEN; University
of Caen; IBFA Laboratory of Biochemistry; Esplanade de la Paix ; 14032 Caen; France 26 Statistics Norway,
0033 Oslo; Norway 27 UKZUZ; Central Institute for Supervising and Testing in Agriculture; Foreign Rela-
tions and EU Department; Hroznová 2; 65606 Brno; Czech Republik 28 Institute of Pharmacy, Faculty of
Health Sciences, University of Tromsø; Norway 29 Central Food Science Research Institute; Herman Otto ut
15; 1022 Budapest; Hungary
Corresponding author: Frieder Graef (fgraef@zalf.de)
Academic editor: K. L. Heong|Received26 August 2011|Accepted 16 March 2012|Published 17 October2012
Citation: Graef F, Römbke J, Binimelis R, Myhr AI, Hilbeck A, Breckling B, Dalgaard T, Stachow U, Catacora-Vargas G,
Bøhn T, Quist D, Darvas B, Dudel G, Oehen B, Meyer H, Henle K, Wynne B, Metzger MJ, Knäbe S, Settele J, Székács
A, Wurbs A, Bernard J, Murphy-Bokern D, Buiatti M, Giovannetti M, Debeljak M, Andersen E, Paetz A, Dzeroski S,
Tappeser B, van Gestel CAM, Wosniok W, Séralini G-E, Aslaksen I, Pesch R, Maly S, Werner A (2012) A framework for a
European network for a systematic environmental impact assessment of genetically modied organisms (GMO). BioRisk
7: 73–97. doi: 10.3897/biorisk.7.1969
Abstract
e assessment of the impacts of growing genetically modied (GM) crops remains a major political
and scientic challenge in Europe. Concerns have been raised by the evidence of adverse and unexpected
environmental eects and diering opinions on the outcomes of environmental risk assessments (ERA).
e current regulatory system is hampered by insuciently developed methods for GM crop safety testing
and introduction studies. Improvement to the regulatory system needs to address the lack of well designed
GM crop monitoring frameworks, professional and nancial conicts of interest within the ERA research
and testing community, weaknesses in consideration of stakeholder interests and specic regional condi-
tions, and the lack of comprehensive assessments that address the environmental and socio-economic risk
assessment interface. To address these challenges, we propose a European Network for systematic GMO
impact assessment (ENSyGMO) with the aim directly to enhance ERA and post-market environmental
monitoring (PMEM) of GM crops, to harmonize and ultimately secure the long-term socio-political
impact of the ERA process and the PMEM in the EU. ese goals would be achieved with a multi-dimen-
sional and multi-sector approach to GM crop impact assessment, targeting the variability and complexity
of the EU agro-environment and the relationship with relevant socio-economic factors. Specically, we
propose to develop and apply methodologies for both indicator and eld site selection for GM crop ERA
and PMEM, embedded in an EU-wide typology of agro-environments. ese methodologies should be
applied in a pan-European eld testing network using GM crops. e design of the eld experiments and
the sampling methodology at these eld sites should follow specic hypotheses on GM crop eects and
use state-of-the art sampling, statistics and modelling approaches. To address public concerns and cre-
ate condence in the ENSyGMO results, actors with relevant specialist knowledge from various sectors
should be involved.
Keywords
GM crops, eld testing network, environmental risk assessment, post-market environmental monitoring,
typology of EU agro-environment, stakeholder involvement, socio-economic impact assessment

A framework for a European network for a systematic environmental impact assessment... 75
Introduction
Cultivation of genetically modied (GM) crops in European agriculture is, compared to
other developed countries, limited due to the signicant public opposition and scientic
research on their potential adverse eects (Lemaire et al. 2010; Myhr 2010; FOE 2011).
e concerns centre on the potential risks of GM crop cultivation, evidenced by adverse
direct or indirect environmental and health eects (Heard et al. 2003; Giovannetti et al.
2005; Relyea 2005, Benachour and Séralini 2009; Graef 2009; Lang and Otto 2010;
Séralini et al. 2011). In relation to potential environmental eects in soil, a number of
unexpected research results have been reported, for instance on the transfer of engi-
neered genes from transgenic plants to soil bacteria (Gebhard and Smalla 1998; Nielsen
et al. 2000), and the release of insecticidal and fungicidal toxins by the roots of trans-
genic plants into the surrounding environment (Saxena et al. 1999; Turrini et al. 2004).
e resulting societal attention to risk demands a robust and independent regula-
tory system. e regulatory system that has evolved is subject to criticism, particularly
with regard to inadequately designed GM crop testing and introduction studies (Hil-
beck et al. 2011), and diering conclusions of the ERAs, for instance with respect to
health risks or nutritional assessment studies due to nancial or professional conicts
of interest (Diels et al. 2011). ere has been insucient attention given to full envi-
ronmental problem-formulation, protection and developmental goals, and other soci-
etal concerns (Nelson et al. 2009). is has fed scepticism. Other factors underpinning
uncertainties in the environmental safety of GM crops that have engendered public
distrust in regulatory practices around GM crops include a) conicting or negative
results of GM crop eects on non-target organisms (NTO) (Castaldini et al. 2005;
Lovei and Arpaia 2005; Rosi-Marshall et al. 2007; Bøhn et al. 2008, 2010), b) lacking
environmental baseline data from prospective GM crop cultivation areas as required
by Directive 2001/18/EC (European Commission 2001), c) poor monitoring designs
(De Jong 2010), d) missing studies and/or data relevant to the approval process (Graef
et al. 2010), e) undesirable impacts on organic farming (Binimelis 2008; Henle et
al. 2008), and f) the diering interpretations of Directive 2001/18/EC among EU
Member State authorities (BfN et al. 2011). Doubts have been raised about whether
the EU regulations, and especially their implementation, appropriately protect pub-
lic interest and goods, and are instead biased towards supporting unsustainable high
input agriculture. e insucient involvement of local stakeholders and insucient
transparency in regulatory processes feed the scepticism about GM crop import and
cultivation, and have led to polarized discussions and strong reactions from the public,
for instance destruction of eld trials (Lemaire et al. 2010).
ese shortcomings are partly related to lack of independent biosafety research and
to prevailing simplistic and sometimes misleading research approaches, which generally
undervalue the complex network of interactions governing ecosystem functions. e
selection of eld sites, indicators, detection methods, assessment schemes and other com-
ponents among the ERA for GMOs often contain a signicant degree of arbitrariness
(Hilbeck et al. 2011). In particular, monitoring of single trait transgenic proteins can be

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
76
burdened with substantial systematic errors (Székács et al. 2010) rendering corresponding
literature data hardly comparable to each other. Such research and monitoring methods
require better standardisation among laboratories (Székács et al. 2011) and should also
respect particular characteristics of the dierent receiving environments. Also, the insuf-
cient consideration of regional particularities (Schermer and Hoppichler 2004; Graef
et al. 2005) and of the socio-economic context of European farming systems (Ohl et al.
2007; Binimelis et al. 2009) in many cases has contributed to questionable relevance of
eld studies submitted in dossiers seeking approval from European authorities for eld
trials, cultivation or import. Previous EU research in this area (European Commission
2010, 2011; Biota 2011) has placed little emphasis on these issues, despite the critical
importance of these aspects for achieving the desired outcomes from the EU Directives.
Requirements and challenges for a European-wide network for system-
atic GMO impact assessment (ENSyGMO)
According to the EU Directive 2001/18/EC, GM crops considered for placing on
the market must be subjected to satisfactory eld testing at research and development
stages in all those ecosystems which could be aected by their use (European Com-
mission 2001). Furthermore, GM crop introduction into the environment must be
carried out following a precautionary approach by using the “step-by-step” principle,
gradually increasing the scale of release if data obtained at previous steps does not
provide evidence for biosafety concerns (Hilbeck et al. 2011). GM crop introductions
in the EU must follow this regulatory framework that requires a systematic environ-
mental risk assessment (ERA) and mandatory post-market environmental monitoring
(PMEM) after approval. While the ERA is primarily based on short-term and small-
scale introduction of the GM crops, PMEM is intended to handle uncertainties about
remaining potential adverse environmental eects after the ERA, comprising immedi-
ate, direct, indirect, delayed, long term as well as combinatorial and cumulative eects
(European Commission 2001). e approval process of GM crops in the EU must
consider both the sustainability of agricultural systems and environmental protection
goals. However, both intentions need long-term interdisciplinary perspectives and sys-
temic assessments, including social and economic ones, for generalising possible GM
crop impacts across the variable European agricultural and environmental conditions
(Ohl et al. 2007; Graef et al. 2010; BfN et al. 2011).
Taking a long-term view and allowing for systematic pre-release and continued
assessments of GM crops introduced into diering receiving agricultural and natural
environments will require that representative indicators are identied, developed, vali-
dated and harmonized with regard to the dierent ecological and socio-economic con-
texts within Europe. Also, detection methods and a process of selecting representative
eld test sites across the biogeographic and agro-ecological regions and socio-economic
contexts of the EU need to be established in a transparent and scientically sound
manner, taking into consideration specic regional protection goals.

A framework for a European network for a systematic environmental impact assessment... 77
To achieve these ends, we propose the establishment of a Europe-wide network
for systematic GMO impact assessment (ENSyGMO) that simultaneously targets the
following core issues:
• Harmonizedandwheneverpossiblestandardizedkeyindicatorsandsampling
methods to quantify possible impacts (EFSA 2010a). is leads to reliable and
comparable data within representative testing sites across Europe and can be
used as a scientic basis for a realistically dierentiated EU-wide ERA.
• Arepresentationofthevariabilityofagro-ecosystemsanditsbiologicalandso-
cio-economic components into which GM crops are proposed for introduction.
• Designofstatisticallyrobustrepresentativeeldtests ontheEuropeanscale,
and protocols for data analysis as a basis for the ERA and PMEM studies.
e challenge here is not so much to ensure the detection of adverse eects in
agricultural systems, but to discriminate measured eects with regard to cause-
eect relationships, for instance potential impact of GM cropping on other
agricultural practices, taking into account also the dynamics of agricultural
and environmental changes.
• Stakeholderinvolvementfori)communicationofeldtestregionsandsites;
ii) feedback from the relevant local actors, such as the farming communities
and bee keepers among others, on the design of comparisons (including iden-
tication of salient indicators) between GM cropping and non-GM cropping
systems; iii) a sound basis for socio-economic assessments and monitoring of
conicts (Henle et al. 2008); and iv) eective dissemination of methods, pro-
cedures and approaches to the administration and decision makers, and other
stakeholders and users.
• Publicandscienticvalidationondevelopment,applicationandimprovement
of ERA procedures and protocols through enhanced stakeholder involvement
and transparency.
We suggest establishing the ENSyGMO framework for the ERA (and in part for
the PMEM) using as the rst cases the GM crops authorised for cultivation and com-
parative assessment with near isogenic lines or other conventional counterparts in re-
gionally diering agricultural systems with specic crop rotations. However, since con-
ventional non-GM agriculture may also create adverse eects, the assessment of these
eects should not be restricted to comparative approaches only, but include additional
sustainability criteria for agriculture and its environment. is will require modica-
tions to existing frameworks. For example, the PMEM design may be inadequate to
cover such eects and will require a more advanced monitoring approach (BfN et al.
2011). ENSyGMO must aim primarily to create trust in its scientic independence,
robustness and societal utility. Accordingly, the participation of relevant stakeholders
from the public sector, researchers, and the private sector is central in the ENSyGMO
approach. Where appropriate this includes attunement of prevailing scientic indica-
tors and parameters to relevant stakeholder (e.g. farmer) knowledge and concerns.

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
78
Objectives of the ENSyGMO framework
e overall goal of the ENSyGMO framework is to design and apply harmonized pro-
cedures for detecting and analysing GM crop eects across the variability of European
agricultural environments and socio-economic contexts. A further key goal is to make
the EU regulatory framework as well as the appraisal of GM crop introduction propos-
als more scientically, socially and technically robust. ese overarching goals can be
broken down into the following objectives:
1) e development of a harmonized catalogue of evaluated indicator organisms,
from both a pan-European and regional view, based on dened criteria for identifying
indicators (e.g. functional groups, traits, communities, red list species, etc.) that cap-
ture possible impacts on biodiversity and other national or regional protection goals.
2) e development and validation of a harmonized catalogue of standardized
sampling, analyses and evaluation methods, as a basis for ERA and for possible long-
term PMEM studies.
3) e creation of a database of current agro-environmental (baseline) character-
istics of the main biogeographic regions in Europe, consisting of a) a biogeographical
inventory of indicator organisms and their variability across European agricultural ar-
eas and b) the typologies of agricultural systems and surrounding environments with
respect to potential GM crop introductions.
4) e design and establishment of a pan-European network of representative sites
tested and veried for ERA, and for long-term PMEM studies and representative for
EU biogeographic regions and farming systems.
5) e analysis of the socio-economic impacts of GM crop cultivation and its
management (e.g. including co-technology such as herbicides used) in relation to the
eco-social context of introduction, non-GM crop cultivation contexts, and regionally
diering agricultural practices.
6) e participation of a wide community of stakeholders representing diverse
social and ecological values and criteria of performance and the communication of the
ENSyGMO framework design, activities and results with all relevant stakeholders and
the public, beyond those already involved.
ese objectives should be designed for regulatory authorities of relevant re-
gional to European levels, eld assessors, farmer representatives, and scientists in the
relevant elds (inter alia agronomy, ecology, and socio-economy). e ENSyGMO
framework also includes an analysis of its potential to expand the network structures
and protocols, for instance the methods to derive appropriate indicators for specic
GM crops. A general task of the ENSyGMO framework is the development, testing
and application of the harmonized ENSyGMO outcomes to serve as a model and
basis for future ENSyGMO renement, and for the development of other network
systems that assess and/or monitor technology and innovation impacts in agricul-
ture, environment and socio-economy, which are still missing in the EU (Henle et

A framework for a European network for a systematic environmental impact assessment... 79
al. 2008; e Royal Society 2009). e results gained by such a network could be
also used for other stressors in agricultural landscapes. For instance, the pesticide
registration procedure in EU requires distinguishing between bio-geographic re-
gions in Europe (European Commission 2009), yet its implementation is seriously
hampered by the lack of basic data on the composition of organism communities
(EFSA 2010b).
Design of the ENSyGMO framework
e ENSyGMO framework must encompass all relevant dimensions for a comprehen-
sive and regionally specic GM crop assessment scheme, including adaptability to fu-
ture scenarios and challenges. For designing and implementing the ENSyGMO frame-
work, we suggest six interlinked ematic Clusters (TC) reecting the main aforemen-
tioned objectives and directly leading to core products (Figure 1). e core products
are: a harmonized catalogue of evaluated indicator organisms and sampling methods
to quantify possible GM crop impacts (TC1); a database of baseline variability of EU
agro-ecosystems (TC2); an EU network scheme for statistically-based representative
eld tests (TC3); a socio-economic impact assessment framework (TC4); public and
stakeholder participation and dissemination, thus improved public legitimacy (TC5);
Figure 1. Interrelationship of thematic clusters (TC) and core products in the ENSyGMO framework:
Indicator and sampling methods are selected (TC1) and baseline data and typology generated (TC2),
which are then integrated and validated in the eld testing network under real agricultural eld condi-
tions (TC3) and the socio-economic context (TC4). Based on the GM crop eld testing results the eld
network is successively adapted to represent the EU typology of European agro-ecosystems and biogeo-
graphic regions (TC2). Field trial results and supplementing GM cropping data, as well as the stakeholder
analysis (TC5), need to be included with the socio-economic impact assessment of the GM crops (TC4).
Between the TCs 1-4 there are feedback loops to iteratively and mutually adapt/improve the ENSyGMO
framework. All themes are integrated, evaluated and synthesised (TC6) to ensure the applicability of EN-
SyGMO products to the ERA, PMEM and SEIA regulatory frameworks.

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
80
and an integration and synthesis of the dierent scientic improvements across these
ENSyGMO domains, (TC6) particularly taking care of the need to transfer the EN-
SyGMO products to the regulatory framework.
Indicators and sampling methods (TC1)
e identication of indicators and sampling methods for detecting potential GM
crop impacts is a crucial step in the ERA methodology. A proposed ERA concept (Hil-
beck et al. 2008a, 2011) that was partially included in the EFSA (2010a) guidelines
places the whole GM organism at the centre of the assessment. e concept includes
potential adverse eects arising from direct and indirect exposure to the GM crop and
also secondary stressors such as inherent management practices to the specic GM
crops (e.g. the application of broad spectrum herbicides) (Andow and Hilbeck 2004).
To achieve a comprehensive and solid foundation for indicator identication, hy-
potheses and evidences about ecological impacts of GM crop cultivation in various
regions and environmental conditions have to be compiled. Both direct and indirect
eects must be covered. Direct eects include, for instance toxic eects on non-target
fauna, mainly invertebrates but also mammals and microbes (Relyea 2005; Giovan-
netti et al. 2005; Benachour and Séralini 2009). Indirect eects refer for instance to
altered rotation and other production schemes, pesticide applications rates and timing,
and tillage system (Graef 2009). Also combinatorial or cumulative eects, for instance
alterations in biodiversity or food webs, and pest-resistance development should be
covered (Heard et al. 2003). Furthermore, the relevant environmental compartments
(terrestrial both below- and above-ground, and aquatic systems) and land-use forms
(agricultural sites and other potential receiving environments) should be represented
(EFSA 2010a; BfN et al. 2011).
Indicators must be then selected in a step-wise process, which begins with iden-
tifying the most important ecological functions and protection goals relevant to sus-
tainability in agriculture and continues with the identication of possible exposure
pathways, relevant species in the local ecosystem, their suitability for testing, their
sampling methods, and their practical testing (Hilbeck et al. 2008b). Such indicators
are a) organisms at the species and/or community level including functional groups
such as earthworms (Bouché 1977), trophic groups such as nematodes (Yeates 2003)
or trait groups such as aquatic invertebrates (Liess and Beketov 2011); b) direct func-
tional endpoints such as litter decomposition, biogeochemical cycles completion; c)
indirect functional endpoints such as ecological functions provided by single species
or communities (Hilbeck 2008a, b; Schmitt-Jansen et al. 2008) and ecosystem ser-
vices such as biodiversity and habitat provision and/or pollinators securing food crop
production (Faber and van Wensem 2012; Mace et al. 2012); and d) landscape-scale
related indicators such as land use diversity which may be aected by altered rotation
and other production schemes (Graef 2009). ey must represent not only arable ar-
eas, but neighbouring receiving environments including wild habitats, where the GM

A framework for a European network for a systematic environmental impact assessment... 81
crops may have a potential impact or could occur. ere should be a representation
of at least a) the main environmental compartments (terrestrial below- and above-
ground, aquatic); b) functional groups such as predators, herbivores, saprophages,
and symbionts; and c) dierent physiological, taxonomical groups, for instance,
mainly arthropods but also oligochaetes, microbes and/or fungi (Hilbeck et al. 2008a;
Römbke et al. 2009).
Detecting possible impacts on indicators requires appropriate laboratory testing
methods suitable for the ERA, as well as eld testing and monitoring methods (Hil-
beck et al. 2006, 2008b; EFSA 2010a). ese methods should be preferentially stand-
ardised, for instance, by OECD, ISO, VDI or IOBC methods (Fink et al. 2006; VDI
2010). Depending on the selected indicator species, these methods may require modi-
cations or new methods must be developed. Sub-lethal endpoints, such as reproduc-
tion, should be included as criteria since they can also give indications of possible
long-term eects and are more sensitive than acute (lethal) harm (Römbke et al. 2009).
e methods identied have to be examined in practice, preferably in inter-laboratory
comparison tests, and developed into a comprehensive testing protocol.
e hypotheses on GM crop eects need to be practically tested using the selected
indicators and laboratory methods. Current ERA procedures are expected to undergo
considerable improvement (EFSA 2010a). Lab tests should be performed with the GM
plant material as well as with mixtures of GM plant and conventional counterpart ma-
terial, and compared to a non-GM conventional counterpart. Test data-sets must be
statistically evaluated to control the test method performance under routine conditions
and to help focus subsequent eld testing (Römbke et al. 2009). Field tests are also
essential in higher tier evaluation, and must be performed, even if the proposed mode
of action is well understood and laboratory tests indicate no observed eect on a given
species (Romeis et al. 2011).
Finally, assessing socio-economic impacts of GM crops in European agro-ecosys-
tems and regions require specic indicators as part of the ENSyGMO framework.
ese indicators need to combine the relevant socio-economic impact assessment
(SEIA) factors, GM crop environmental monitoring data, and the associated agricul-
tural management practices (Henle et al. 2008). Using regional rules derived inter alia
from the research we propose and/or scenarios for identication and measurement of
socio-economic indicators is particularly useful, for instance, relating to management
or co-existence inputs of GM crops compared to non-GM crops, in the specic eco-
social context of the GM crop receiving environment (Binimelis 2008).
Baseline conditions of European agro-ecosystems (TC2)
In 2008, the European Commission mandated the EFSA to develop methodologies
and recommendations for establishing relevant GM crop baseline information. e
guidance (EFSA 2010a), however, does not yet provide substantial improvement in
this regard. Europe covers a wide range of agro-environmental conditions, which are

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
82
reected in a wide variety of agro-ecosystems with specic biodiversity, climate, land
use and management systems and agricultural productivity. Spatial classication of
information and geographical data is essential for their analysis and communication
(Metzger et al. 2005). Increased availability of spatial environmental data and ad-
vances in spatial data processing has led to a range of new European classications
and typologies of biophysical regions (Hazeu et al. 2011; EEA 2011). However, few
attempts have been made to develop useful classications and/or typologies focus-
sing on environmental impacts of agricultural innovations. is requires the linkage
of information on farming systems and information on the biophysical endowment
(Kempen et al. 2010).
For the ENSyGMO framework, we suggest establishing a comprehensive spatial
agro-ecosystems typology and regional baselines of EU agro-landscapes and the wider
potential receiving environments. is should build on or be co-developed with ex-
isting stratications, typologies and classications (Andersen et al. 2007; Petit et al.
2008; Hazeu et al. 2011; EEA 2011) with biophysical data relevant for discriminating
potential environmental GM crop eects on the previously identied indicators (TC1)
from the continuously changing agro-environment. Ecological information on habi-
tats, species, sites with local biological diversity importance, and protected areas should
also be integrated. Scale-related omissions in geographic regions represented, habitats,
ecosystems and taxa must be identied throughout the ENSyGMO framework in
order to collate additional data if possible (Dalgaard et al. 2003).
Baseline information primarily for the aforementioned environmental and socio-
economic indicators must be compiled at the European level to eciently assess the
sensitivity of European regions and agro-ecosystems, particularly in relation to poten-
tial adverse eects of GM crops within diering protection, developmental and socio-
economic goals (Dziock et al. 2006). Other baseline information and indicators are
essential for explaining GM crop eects. ese may relate, for instance, to characteris-
tics of farming systems, biophysical and ecological conditions for agro-ecosystems, and
protected wildlife and habitats, and ecosystem functions (Settele and Kühn 2009; Bi-
ota 2011; Jänsch et al. 2011), and should refer to EEA and OECD standards (OECD
2008; EEA 2010). Established environmental monitoring programmes (EMP) may
also provide baseline information needed for targeting eld sites and for eld testing.
EMPs are established and integrated, for instance, under the Water Framework Di-
rective, the Habitats Directive (Graef et al. 2008) and for the Long-Term Ecosystem
Research Network sites (LTER 2011) but exist also at the national level (Schmeller
and Henle 2008; EuMon 2011).
e ENSyGMO baseline information on European agro-ecosystems must be
managed and analysed with a geo-database including onthology, its access, main-
tenance and meta-data information. is geo-database should include the spatial
agro-ecosystems typology and the indicators determined (Andersen et al. 2007), and
should be accessible through standard database browsers and (Web-)GIS-programmes
(Kleppin et al. 2011).

A framework for a European network for a systematic environmental impact assessment... 83
EU wide network for GM crop eld testing and monitoring (TC3)
Practical eld testing and PMEM in the EU and worldwide are lacking a scientically
robust and spatially representative design (BfN et al. 2011). GM crop introduction
trials in general are concentrated on one or a few locations only and are restricted to
short-term studies (Lövei and Arpaia 2005). ese shortcomings, together with the
fact that GM plant approval dossiers sometimes crucially rely on tests done in non-EU
overseas regions are major reasons for public concerns and for the often contradictory
comments of EU Member State experts during GM crop application and decision-
making processes (Graef et al. 2010). e only larger scale experiments conducted this
far in the EU are the Farm Scale Evaluations in the UK (Firbank et al. 2003, Heard et
al. 2003). us, the step-by-step principle of gradual spatial increase of the GM crop
introduction as required by Directive 2001/18/EC (European Commission, 2001) is
not implemented in practice. Methodologies for designing regionally representative
eld tests are scarce (e.g. Stein and Ettema 2003; Graef et al. 2005); and networks for
carrying out these studies do not exist yet. Both ERA and PMEM require a representa-
tion of the variable European agro-environment (EFSA 2010a). erefore, we consider
that the implementation of a comprehensive network approach such as the ENSyG-
MO in the near future is critical to address these deciencies in current practice.
Given the inherent agro-biodiversity in the EU a fully functioning representative
network cannot be implemented right from the start. Rather, initially this has to be
a prototype requiring incremental adaptations and renements, based on eld test-
ing results and multi-/trans-disciplinary experience gained (Lindemayer and Likens
2009). Hence, the proposed ENSyGMO must be based on a statistically veried ex-
perimental eld study design comprising a test site network. Being based on the agro-
environmental baselines and typologies developed, this design should have sucient
power to explain the EU-wide variability of dierent indicators. e network should
not only cover present GM cultivation regions (FOE 2011) but include environments
where potential future GM crop cultivation could take place. Existing eld test sites
of agricultural companies and/or authorities and of agricultural research institutions
could provide the core of such a network (Figure 2). e initial design, depending on
the typology outcome, may include 8–10 sites including sucient replications (Figure
2). To achieve public acceptance of the GM crop cultivation and the assessment pro-
cess the involvement of local or other stakeholders into design and conducting the eld
experiments is crucial (Lemaire et al. 2010).
Practical eld testing using established indicators and sampling methods should be
done under controlled conditions in parallel at all sites. ENSyGMO sites will also serve as
facilities for socio-economic impact assessments (SEIA). To assess laboratory and eld lev-
el indicators and methods for their suitability and extrapolation, eld testing in additional
GM crop cultivation regions outside Europe, for instance those with signicant levels of
GM crop cultivation, (e.g. Brazil, India and China) should be undertaken. It is expected
that at least the same taxonomic or functional groups can be used in the dierent areas.

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
84
Managing the ENSyGMO eld testing data requires a well-designed database, one
that can be used to analyse the ENSyGMO data in present and future ERA and PMEM
assessments (Reuter et al. 2010) and also store additional data collected from various
sources. e data may also be used for feeding decision support systems with appropriate
inputs and for creating predictive models from the eld testing data (Bohanec et al. 2008).
To achieve sustainability of an ENSyGMO framework, structural, nancial, and
organisational requirements need to be identied. is analysis should also include
the potential for other institutions with wider environmental, ERA and monitoring
expertise to co-operate and give further methodological input. For long-term establish-
ment of the ENSyGMO sites, local or other relevant stakeholders are expected to be
involved (Lemaire et al. 2010).
Socio-economic impact assessment (TC4)
Analysis of the current research shows that a signicant amount of work on SEIA is nar-
row in scope and contested in terms of assumptions, applied methodologies and nd-
ings (Desquilbet and Bullock 2009; Demont et al. 2010; Glover 2010). We nd that:
Figure 2. Potential distribution of research institutions and available eld research stations in an EN-
SyGMO representing the Environmental Stratication of Europe (Metzger et al. 2005). Field station
sites for practical testing of GM crops should be located in all agro-ecosystems relevant for GM cropping.

A framework for a European network for a systematic environmental impact assessment... 85
• mostsocio-economicimpactresearchfocusesonex-anteandpurelyeconomic
parameters of a limited number of GM crops cultivated in only a few regions,
which creates a knowledge gap on the actual impacts after GM crops are intro-
duced into the environment (Smale et al. 2009);
• comprehensive comparative analysis between GM and non-GM crop pro-
duction systems (e.g. conventional, GMO-free, organic) along the produc-
tion chain and implications of co-existence (Coléno 2008) are missing. is
approach includes the analysis of entangled socio-economic and ecological
relationships. For instance, potential undesired processes, such as gene ow
resulting in transfer of GM pollen to honey, may have implications at the
commercial (e.g. honey with GM pollen would require a specic authorisa-
tion for its consumption) (European Court of Justice 2011), managerial (e.g.
beekeepers moving their bee colonies to other areas to avoid contamination)
(Lezaun 2011), and the ecological level (e.g. displaced bee colonies may sig-
nicantly reduce pollination of plants in agricultural and natural ecosystems);
• socio-economicimpactsthatmightgobeyondthemonetaryassessmentanaly-
sis are rarely considered (Binimelis 2008);
• usuallyadequate costs andbenets analyses areunfeasible, due torestricted
knowledge on both potential adverse eects and benets of GM crops in the
medium and long term (Messéan et al. 2009);
• integratedsocio-economic analysis with respect toother impacts,including
unintended environmental eects, usually is ignored (Pavone et al. 2011);
• onlyasmallcommunityofresearchersisinvolvedinSEIA,restrictingthevari-
ety of research perspectives and narrowing the range of methodologies mainly
to agro-economic aspects such as yield, prices, cost of production, prots and
consumer acceptance (Smale et al. 2009).
ese shortcomings are tackled in the ENSyGMO framework in light of the
recognition of the multifunctionality of agriculture (e Royal Society 2009), by a)
including the intertwined relationship between the ecological and socio-economic
context where GM crops are introduced, and b) facilitating the participation of
relevant stakeholders as central in the ENSyGMO methodological approach for a
comprehensive SEIA.
Accordingly, the SEIA of the ENSyGMO framework includes, in a rst step, de-
ning potential or observed adverse socio-economic impacts of GM crops. is is
based on a) an analysis of the existing cases of GM crop introductions, b) existing
information and knowledge provided by integrated SEIA methods and experiences,
c) analysis of the socio-cultural and institutional context of GM crop introductions,
taking into account the private sector (farms, traders, supply chains) and the public
sector (national, regional governments and communities), d) identication of protec-
tion goals in relation to socio-economic welfare and sustainable development, and e)
identication of relevant knowledge gaps.

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
86
e SEIA framework of GM crops must be developed from the baseline informa-
tion obtained prior to or simultaneous with their introduction. is includes consulta-
tion with relevant private and public sector stakeholders. In the ENSyGMO frame-
work, relevant stakeholders refer to the dierent actors along the GM crop value chain
that are aected in monetary and non-monetary socio-economic terms and include,
inter alia, GM and non-GM farmers, the agribusiness sector (e.g. importers of inputs
for GM crop production and traders), local communities and families surrounding
the GM crop cultivation, consumers, policy and decision makers, and practitioners
of SEIA. e SEIA consultation process includes the identication of a) relevant en-
vironmental, cultural, institutional and political factors with socio-economic impacts;
b) socio-economic and development protection goals, c) monetary and non-monetary
implications at farm and community level (TC6); and d) a decision support system for
a comprehensive and comparative assessment of socio-economic impacts of GM crops.
Finally, the SEIA of the GM crops tested within the ENSyGMO framework need
to be validated. is requires the implementation of the SEIA on the value chain of
the GM crops under the EU relevant scenarios, taking into account the regional spe-
cicities, environmental and socio-economic protection goals and data availability in
dierent test site regions. Moreover, complementary studies in GM crop commodity-
exporting countries such as Argentina or Canada should be included in order to attain
a more comprehensive knowledge base on the interrelated socio-economic pathways.
Adaptations of the SEIA framework based on the experience gained from implementa-
tion and feedback from actors and stakeholders involved, and integration in terms of
approach, ndings, lessons learned and policy recommendations, would be the nal
steps in this framework.
Communication and dissemination in the ENSyGMO framework (TC5)
e benets and potential adverse eects of GM crops are highly contested in the sci-
entic, public and policy spheres. In these debates environmental and socio-economic
harm has typically been viewed as a purely scientic matter. In the framing of harm,
benets and risks the analysis of social conditions (Myhr 2010) and human values
(Wynne 2001) also are considered. ese are relevant for assessing impacts (Felt et al.
2007) as it corresponds to the Problem-Framing within the Problem Formulation and
Options Assessment (PFOA) framework for ERA (Nelson et al. 2009). e ENSyGMO
framework recognizes the importance of the social, cultural and ethical factors relevant
to dierent actors and stakeholders. As a result the framework includes a two-way com-
munication approach as an essential component of good scientic research practice, as
well as for social and ethical considerations in policy and decision making (Dalgaard et
al. 2003). is allows a multi-sector and multi-disciplinary dialogue among the major
groups of stakeholders (i.e. private sector / policy-makers / researchers / civil society).
Communication within the ENSyGMO framework takes place in various forms,
including information provided through scientic conferences and other meetings,

A framework for a European network for a systematic environmental impact assessment... 87
scientic journals, policy reports and technical reports, also more proactive exchange
of knowledge (e.g. workshops). Moreover, the ENSyGMO methodology and results
– being cross-cutting issues – should be actively communicated to the full range of
GM crop ERA and SEIA practitioners, for instance, the European Commission and
national Competent Authority scientists, environmental agencies, land managers, and
policy-makers.
Communication in the ENSyGMO framework must also include pre-assessment
communication. is should refer to the dissemination of project aims, particularly
eld trial objectives, design, requirements, and envisaged uses in conjunction with
the other ENSyGMO framework actors through a) an early-established multi-lingual
interactive website that is regularly updated and informs scientists, policy-makers, au-
thorities, NGOs and the interested public and also elicits public and other stakeholder
responses, and b) stakeholder-dialogue meetings in selected Member States (Myhr
2010). Long-term commitments of local and other stakeholders need to be established
for conducting the eld trials and the agro-environmental and socio-economic moni-
toring.
Stakeholder knowledge and concerns should be included in the assessment plan-
ning itself (Wynne 2001). Both public and private stakeholder knowledge and con-
cerns about GM crops and site-specic or more widespread potential hazards, which
could contribute to the scientic ERA and the SEIA, need to be retrieved. is requires
analysis of the ENSyGMO interactive website, analysis of responses from the stake-
holder dialogue meetings, the combined evaluation of the ENSyGMO lab, eld test
and SEIA results, and application of the PFOA framework (Nelson et al. 2009). It also
requires input from GM crop cultivation scenarios (TC6), and from EFSA stakeholder
and public consultation processes (Koutalakis et al. 2007).
e ENSyGMO framework should include training and capacity building through
approaches adapted to the dierent audiences, targeting a) the broad range of actors
and stakeholders; b) practitioners including social scientists, especially at postgraduate
levels; and c) EU, Member States and developing country policymakers. e purpose
is to provide understanding of the nature and conduct of such eld trials and assess-
ments necessary to satisfy GM crop regulatory requirements.
Integration, evaluation and synthesis in the regulatory context (TC6)
e interpretation and implementation of the ERA and PMEM principles, as laid
down in Directive 2001/18 and Annex III of the Cartagena Protocol, is an ongoing
process dening and rening what is needed and how it can be achieved (Hilbeck et
al. 2008a,b, Myhr 2010, BfN et al. 2011). Scientic, legislative and regulatory re-
quirements, as well as societal or political perceptions, frame the ERA, PMEM and
the SEIA. e ENSyGMO framework aims at providing sound data with the eld
studies for the ERA and PMEM, providing appropriately harmonised and, if possible,
standardised methods and indicators for detection and analysis (VDI 2010). It aims at

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
88
transferring the ERA mainly based on short-term observations to an ecosystem-based
integrated assessment of the GM crop impact on the farming systems, environment
and socio-economic context specics. e ENSyGMO framework also requires con-
tinuous review and adaptation including and targeting new and/or unforeseen devel-
opments, new knowledge, and change in cultivation practice and eld sites in the EU.
Accordingly, the ENSyGMO framework is an iterative process for constantly review-
ing and improving research hypothesis and methods in the ERA, PMEM and SEIA.
Hence, an integrating platform is required to create maximum impact and usabil-
ity of core ENSyGMO products (Figure 1) for the existing ERA, PMEM and SEIA
frameworks. is platform requires the permanent involvement and inputs of all EN-
SyGMO partners and vice versa. e core objective of this platform is the development
and synthesis of a comprehensive, interdisciplinary scenario framework for GM crops
adoption and associated changes in EU agriculture. is is based on inputs by the EN-
SyGMO actors and themes (indicator organisms, sampling methods, baseline require-
ments, overall network design, socio-economic impact, stakeholder dialogue) and on
previous or ongoing EU scenario oriented projects, for instance, ALARM, SEAMLESS
and SENSOR (Rounsevell and Metzger 2010). e scenario framework should be
applied to check the usability and predictive power of the ENSyGMO results and for
deriving suggestions for the ERA, PMEM and SEIA frameworks. For instance, GM
crop cultivation scenarios could serve to extrapolate the results on eld testing, regional
protection goals, and regional farming systems to possible future situations.
e ENSyGMO lab and eld studies require synthesis and comparison to other
GM crops, and other studies (including peer-reviewed literature) to attain an overall
ERA, PMEM and SEIA of GM and non-GM farming systems in the EU. is entails
the following steps, a) process-related ndings using tested assessment methodologies
and protocols from lab and eld trials. e pros and cons, as well as required technical,
nancial and person-power input of each methodology should be analysed and recom-
mendations for use formulated; b) synthesis of lab and eld trial data and results using
state-of-the-art statistics. e predictive power of lab studies indicating environmental
impact need to be evaluated by modelling and comparing the ENSyGMO and other
lab data to eld ndings; c) evaluating remaining uncertainties and their impact on the
accuracy of the ERA; and d) the evaluation of lab and eld trial and other data using
the SEIA framework.
e transferability of the ENSyGMO framework results to the existing ERA,
PMEM and SEIA framework in the EU and the Cartagena Protocol on Biosafety has
to be ensured. erefore, the TCs should be monitored and supported from the begin-
ning to provide appropriate baseline information, methodologies and input to exist-
ing protocols. e ENSyGMO outputs require synthesizing and fullment of their
objectives for use by decision makers and relevant stakeholders on regional, Member
States, European and global scales. e nal recommendations require a consensus-
building process within the ENSyGMO framework. Representing dierent interests
of diverse groups in society and regulatory science requires transparency, accountabili-
ty and participation of stakeholders along the ENSyGMO implementation. A series of

A framework for a European network for a systematic environmental impact assessment... 89
stakeholder meetings are required for applying and enhancing the PFOA methodology
(Nelson et al. 2009). Finally, the PFOA needs to be tested as a tool for accompanying
eld introduction trials and PMEM by validating the outcomes of the ERA against the
initial ERA assumptions.
Outlook
e ENSyGMO framework endeavours to address the many concerns about GM
cropping systems. ese concerns centre, for instance, on inadequately designed GM
crop testing studies and PMEM, the lack of environmental baseline data and repre-
sentativeness, non-consideration of regional environmental and socio-economic spe-
cics, the conicting interpretation and under-implementation of EU regulations, and
the poor involvement of local and other stakeholders. It is, however, neither a “cure-
all” for addressing conicts, nor can it provide answers to all uncertainties connected
to GM agriculture. However, the ENSyGMO can provide a long-term scientically
sound basis for the ERA of GM crops and for long-term monitoring studies in the EU.
For the proper PMEM as dened by the EU Directive 2001/18/EC additional sites
in real GM cropping regions and farming systems are required, generally with a more
prolonged timeline. e ENSyGMO framework as proposed in detail here requires
eld implementation and validation to eectively contribute to broadening the scope
of requirements and potentials linked to the ERA, PMEM, SEIA and the regulatory
framework of GM crops. ENSyGMO is a exible framework that will be improved
based on the experience gained, the changing contexts and the development of novel
GM crops. As a result and taking into account that the framework operates on a case-
by-case and step-by-step basis, an additional outcome of ENSyGMO is the potential
for organizing permanent or ad hoc expert working teams or sub-networks, depending
on the GM crop (e.g. Bt-Maize working teams) or the potential impacts (e.g. biodi-
versity or socio-economic impacts working team). e ENSyGMO framework is not
only applicable to GM crop impact assessment, but to assessing and monitoring the
implementation, impact and sustainability of EU policies and/or impacts of other ag-
ricultural technologies and innovations, (e.g. synthetic fertilisers, harvesting systems,
plant protection products and the production of non-food crops). In particular, the
ERA of plant protection products, currently under review, would clearly benet from
the activities in the ENSyGMO framework.
Acronyms
EEA European Environment Agency
EFSA European Food Safety Authority
ENSyGMO European Network for Systematic GMO impact assessment
ERA environmental risk assessment

Frieder Graef et al. / BioRisk 7: 73–97 (2012)
90
GMO genetically modied organism
IOBC Int. Organisation for Biological Control of Noxious Animals and Plants
ISO International Organization for Standardization
OECD Organisation for Economic Co-operation and Development
PFOA Problem formulation and options assessment
PMEM post-market environmental monitoring
SEIA socio-economic impact assessment
TC thematic cluster
VDI Verein Deutscher Ingenieure
Acknowledgments
Funding from the Federal Ministry of Food, Agriculture and Consumer Protection
(BMELV) and the Ministry of Infrastructure and Agriculture (MIL) Brandenburg has
supported this work. is article is the outcome of a consortium of authors sum-
marizing their jointly developed concept for a pan-European framework for the sys-
tematic assessment of GMO impacts (ENSyGMO) submitted to the 7th Framework
Programme of the European Union. While another project was selected for funding,
the consortium members wished to put the outcome of their joint eort forward for
further discussion and possible uptake or inspiration to a wider community of sci-
entists, regulators and interested stakeholders. We maintain that such a network is
urgently needed not only for GMO impact assessment but also for other agricultural
policies that require science-based EU-wide oversight. We also would like to express
our gratitude for the critical and constructive comments received by three anonymous
reviewers.
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