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7/30/2019 3464 Valuating Environmental Impacts of Genetically Modified Crops OA
http://slidepdf.com/reader/full/3464-valuating-environmental-impacts-of-genetically-modified-crops-oa 1/194
Olivier Sanvido, Andreas Bachmann,
Jörg Romeis, Klaus Peter Rippe, Franz Bigler
Valuating environmental impacts of
genetically modified crops – ecological
and ethical criteria for regulatory
decision-making
7/30/2019 3464 Valuating Environmental Impacts of Genetically Modified Crops OA
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7/30/2019 3464 Valuating Environmental Impacts of Genetically Modified Crops OA
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Valuating environmental impacts of
genetically modified crops – ecological
and ethical criteria for regulatory
decision-making
7/30/2019 3464 Valuating Environmental Impacts of Genetically Modified Crops OA
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7/30/2019 3464 Valuating Environmental Impacts of Genetically Modified Crops OA
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Valuating environmental impacts of
genetically modified crops – ecological
and ethical criteria for regulatory
decision-making
Olivier Sanvido *
Andreas Bachmann +
Jörg Romeis*
Klaus Peter Rippe +
Franz Bigler *
* Forschungsanstalt Agroscope Reckenholz-Tänikon ART
+ Ethik im Diskurs gmbh
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der wissenschatlichen Forschung.
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Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliograe;
detaillierte bibliograsche Daten sind im Internet abrubar über http://dnb.d-nb.de.
ISBN 978-3-7281-3443-1 (Printausgabe)Download open access:
ISBN 978-3-7281-3464-6/DOI 10.3218/3464-6
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© 2012, vd Hochschulverlag AG an der ETH Zürich
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TaBle o coNTeNTs
..........................................................................................................................................................
1 eXecUTIVe sUMMaRY 9
..........................................................................................................................................................
2 INTRoDUcTIoN 15
2.1 Existing denitions o environmental damage 16
2.2 Diculties to apply existing criteria or environmental damage 18
2.3 Research questions and goals o the project 18
2.4 Relation between ethics and ecology in the context o the given research question 19
2.5 Methods and approaches o the project 212.6 Outline o the report 23
..........................................................................................................................................................
3 a GeNeRal DeINITIoN o DaMaGe 27
..........................................................................................................................................................
4 cHaRacTeRIZING THe PRoTecTIoN Goal “BIoDIVeRsITY” 33
4.1 Background 34
4.2 What is biodiversity? 344.3 Environmental protection goals as specied by Swiss legislation 38
4.4 The ecological relevance o biodiversity 42
..........................................................................................................................................................
5 oPeRaTIoNal DeINITIoN o PRoTecTIoN Goals 49
5.1 Diculty to nd an unambiguous denition o the term biodiversity 50
5.2 A matrix or an operational denition o biodiversity in agricultural landscapes 51
5.3 Application o the matrix or an operational denition o protection goals 57
..........................................................................................................................................................
6 THe Use o “THResHolDs” To eValUaTe RIsKs aND cHaNces 69
6.1 Thresholds in ethics 70
6.2 Thresholds in ecology 72
6.3 Using thresholds in regulatory decision-making 75
..........................................................................................................................................................
5
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..........................................................................................................................................................
7 a IRsT BaselINe aPPRoacH – DIeReNTIaTING eecTs o DIeReNT PesT 79
MaNaGeMeNT PRacTIces IN MaIZe
7.1 The challenge o selecting an appropriate baseline 80
7.2 Case study 1: Eects o Bt-maize on nontarget arthropods 81
7.3 Approach to dierentiate eects o various pest management practices 87
on nontarget arthropods
..........................................................................................................................................................
8 a secoND BaselINe aPPRoacH – DIeReNTIaTING eecTs o DIeReNT 107WeeD MaNaGeMeNT PRacTIces IN MaIZe
8.1 Dierences to the case study with Bt-maize 108
8.2 Case study 2: Eects o GMHT maize on armland biodiversity 108
..........................................................................................................................................................
9 eTHIcal ReeReNce sYsTeM To assess BIoDIVeRsITY 121
9.1 The deciencies o the Ethical Matrix 122
9.2 Introduction to the ethical reerence system 126
9.3 Explanations on the ethical reerence system 1279.4 Application o the proposed approach 138
..........................................................................................................................................................
10 RecoMMeNDaTIoNs oR DecIsIoN-MaKeRs 143
10.1 Ethical considerations when evaluating eects o GM plants 144
10.2 Protection goals 145
10.3 Thresholds 146
10.4 Comparative assessments and baselines 147
10.5 Weaknesses o the regulatory system or GM crops 14910.6 Regulatory burden or GM crops 150
10.7 Acknowledgements 151
..........................................................................................................................................................
11 ReeReNces 153
..........................................................................................................................................................
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..........................................................................................................................................................
aNNeXes 165
ANNEX 1: LIST OF WORKSHOP PARTICIPANTS 166
ANNEX 2: WHAT IS RISK? 169
..........................................................................................................................................................
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eXecUTIVe sUMMaRY CHAPTER 1
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1 eXecUTIVe sUMMaRY
The legal ramework regulating the approval and use o genetically modi-ed (GM) plants demands that regulatory decisions determine what kind o
environmental changes are relevant and represent environmental damage1.
The current debate on the impacts o GM crops on biodiversity illustrates
that consensus on criteria2 that would allow a commonly accepted evalua-
tion o environmental damage is presently lacking. Especially in Europe, GM
crops have been a constantly debated issue, and the interpretation o scien-
tic data is controversially discussed by the dierent stakeholders involved.
Considering the vast amount o scientic data available, one can argue that
the current debate is not primarily due to a lack o scientic data, but more toa lack o clear criteria that allow one to put a value on the impacts o GM crops
on biodiversity.
Ultimately, any decision by regulatory authorities on what they judge being
unacceptable is based on the relevant legal rameworks. Usually, such decisions
are taken in a political context that weighs scientic, ethical and economical
criteria with cultural, religious, aesthetic and other relevant social belies and
practices. Terms such as risk and saety are linked to a conception o damage.
Damage, however, cannot be dened on a purely scientic basis. The normative
character o the term “damage” implies that both choice and denition o whatconstitutes a risk are impossible without a value judgment. Damage has thus
to be dened together with an ethical evaluation as ecological analyses alone
cannot discover “correct” or “objective” criteria or damage.
The project VERDI (Valuating environmental impacts o GM crops – ecolog-
ical and ethical criteria or regulatory decision-making) is an interdisciplinary
collaboration between environmental biosaety and ethics that intends to oer
European policy-makers and regulatory authorities guidance on how decision-
making related to GM crops could be improved. Concentrating on environmental
impacts o GM crops on biodiversity, the project addresses both the ecologicaland the ethical questions involved in nding an operational approach to the
evaluation o environmental damage.
Two case studies with the currently most prevalent GM traits (insect-resist-
ance based on Bt and herbicide tolerance) are used to discuss the open questions
involved. Considerable scientic data on the environmental impacts o these two
traits have been gathered in the past 15 years, allowing one to determine how
such an evaluation could be perormed to be generically applicable to dierent
types o GM crop traits, including new applications o biotechnology.
1 In the ollowing, the two terms “damage” and “harm” are used interchangeably
2 The term criteria is used hereater in the sense o a standard on which a judgment
or decision ma e based.
10
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Stakeholders rom dierent European countries including regulatory authorities, agricultural biotech companies and academia were invited to two
expert workshops. In the rst workshop, current approaches and challenges
in the regulatory decision-making process related to GM crops were analyzed.
The second expert workshop aimed at determining what particular eects o
GM crops on biodiversity are to be judged as unacceptable harm based on an
ecological and an ethical valuation comparing eects o GM crops on biodi-
versity to environmental eects o current agricultural management practices.
Results and eedback obtained during the work-shops were used to elaborate a
synthesis o the relevant ethical and ecological aspects when evaluating impactso GM crops on biodiversity.
The results obtained reveal that both protection goals and baselines are
two consistently emerging issues when discussing a denition o damage.
Protection goals as specied by existing legislation are the exclusive starting
point or a denition o damage or regulatory authorities. Yet, the legislative
terms to describe the protection goal “biodiversity” are too vague to be scien-
tically assessed. Two matrices are proposed to address this problem. The rst
matrix introduces the Ethical Reerence System (ERS), being the rst step in
a systematic process aiming at the specication and justication o plausibleethical criteria to evaluate the risks o GM crops on biodiversity. The second
matrix allows or an operational denition o biodiversity by speciying the
areas o protection as well as assessment and measurement endpoints based
on a number o dened criteria. While the initial proposal regarding what to
protect has to be ramed by the regulatory authorities, the operational deni-
tion o protection goals should be dened in a transparent process involving a
dialogue between all relevant stakeholders. The presented matrix can thereby
be used as a tool to structure the dialogue, especially when dening both assess-
ment and measurement endpoints. The process could include stakeholder meet-ings where stakeholders would compile and rank dierent conservation goals
and ecosystem services.
Baselines are recognized to be the second crucial point in decision-making
processes as they determine what makes a change to be damage. Due to their
vague denition, the use o baselines as a decision support tool nevertheless
remains ambiguous, necessitating a more precise characterization. Common
to all baseline denitions is the term “comparison.” Theoretically, decisions
are always taken relative to a comparator that determines the current practice
EXECUTIVE SUMMARY 11
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that is judged being acceptable. According to this baseline conception, theimpact o a specic technology can only be compared i the impacts o current
practices are known. However, as GM and non-GM-based management prac-
tices are regulated according to dierent regulatory rameworks in Europe, a
direct comparison o the eects o a GM cropping system to its conventional
non-GM counterpart is impossible under the current Swiss and EU regulatory
rame-work. The baseline approach is thus principally not always applicable
as, or example, the EU regulations demands that one assess potential indirect
or cumulative long-term eects o GM crops while this is not a requirement or
conventional pest management practices. Nevertheless, an important point toconsider in such a comparison reers to the act that all regulatory rameworks
dierentiate between “intended” eects o a specic management practice and
“unintended” eects that are to be minimized. This dierentiation allows or
the outlining o a generic scheme that permits one to evaluate whether the
eects o dierent agricultural management practices are to be regarded as
intended eects (which are judged acceptable) or as unintended eects that
could represent environmental damage. This dierentiation may help to over-
come the principal diculties o the initial baseline conception. In a rst case
study with Bt-maize, a fow chart is presented that can help risk assessors todierentiate the eects o various pest management practices used or Euro-
pean Corn Borer management in maize on the arthropod auna in agricultural
landscapes.
In a second case study with GM herbicide-tolerant maize, criteria or regu-
latory decisions or noninsecticidal GM crops were determined. In contrast to
Bt-maize, the assessment o the direct eects o the genetic modication is not
the primary concern or noninsecticidal GM crops. Rather, changes in agricultural
management may be the primary cause o possible indirect eects on armland
biodiversity. The evaluation o indirect impacts prior to approval o the GM cropis challenging. It might be dicult to perorm such an evaluation within the time
rame normally available or pre-market risk assessment as long time periods
are usually needed or indirect environmental changes to become apparent.
These types o eects might, moreover, only become apparent during the large
scale cultivation o GM crop events under real agricultural management. The
establishment o risk mitigation measures thus appears to be a valid option to
increase the level o saety. The goal o these risk mitigation measures should be
to avoid the risk o reduced crop yields and the long-term build-up o problematic
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weed communities while supporting a sustainable degree o armland biodi- versity. Four risk management options are proposed that can help to achieve
a balance between agricultural production and the support o desired noncrop
plants in arable elds.
All technologies that could potentially harm the environment should be
evaluated according to the same legal criteria, or example, according to their
novelty and not to the process o their development. Hence, what constitutes
environmental damage should not be dened by the technology causing it,
but by the type o damage that should to be avoided. The elaborated ethical
and ecological criteria herein may allow a generally acceptable evaluation o damage that can be applied to a wide range o dierent GM crops. The criteria
could help regulatory authorities to improve decision-making and to take
more accurate and coherent decisions. This may ultimately avoid decisions
on environmental risks o GM crops being arbitrary in comparison to other
technologies.
EXECUTIVE SUMMARY 13
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INTRoDUcTIoNCHAPTER 2
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2 INTRoDUcTIoN
2.1 exiting dinitin nvirnmnt dmg
The legal rameworks regulating the approval and use o GM crops require regu-
latory authorities to decide what kind o environmental changes are relevant
and represent environmental damage.3 The current debate on the impacts o
GM crops on biodiversity illustrates that consensus on criteria that would allow
a commonly accepted evaluation o environmental damage is presently lacking.
Especially in Europe, GM crops have been a constantly debated issue and the
interpretation o scientic data is debated controversially by the dierent stake-
holders involved. Considering the vast amount o scientic data available, onecan argue that the current debate is not primarily due to a lack o scientic data,
but more due to a lack o clear denitions regarding how to put a value on the
impacts o GM crops on biodiversity.
Given the complexity o the questions involved, a concise and commonly
accepted denition o “environmental damage” is currently missing. A number o
denitions have been proposed (Box 1) that all entail some challenges regarding
their practical application (see section 2.2).
Common to all proposed denitions are the ollowing three eatures:
• Damage is occurring to a natural resource or resource service such as theconservation and sustainable use o biodiversity,
• Damage is measurable by some means,
• Damage is characterized by an adverse change that is either signicant,
severe or exceeding the natural range o variability
The common eatures lead to three main questions that need to be
answered when approaching a denition o environmental damage. These
questions are not addressed in sucient detail in the existing denitions
mentioned above: • What needs to be protected?
• What is to be measured?
• What is adverse?
To answer the rst question, one needs to dene the protection goals that
should not be harmed and more particularly one must to nd an applicable de-
nition o the concept o biodiversity. It can be noted that the concept o biodi-
versity is well dened in theory, though there are a number o diculties that
3 In the ollowing, the two terms “damage” and “harm” are used interchangeably.
16
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2.2 Diiuti t ppy xiting ritri r nvirnmnt dmg
The diculty to nd an unambiguous denition o environmental damage is
primarily due to the challenge o applying the criteria that have thus ar been
proposed to assist regulatory authorities when evaluating environmental damage
in actual situations o decision-making. A number o authors have proposed
to evaluate damage according to criteria such as “spatial and temporal extent,”
“severity” and “reversibility” o eects (Ammannet al., 2000; ACRE, 2002; Nöh, 2002)
Decisions determining whether observed eects ulll the proposed criteria
or environmental damage are dicult to take due to methodological limits indata collection and analysis. Scientic methods are only partially capable o
adequately evaluating the magnitude o change o a particular environmental
resource. Environmental sciences can help to assess the abundance o a partic-
ular species group, but it is usually dicult to determine whether an observed
change in a species group is exceeding the natural variation o the species group.
This is because appropriate baseline data is oten lacking and because agro-
ecosystems are dynamic and subject to constant change. Long time periods are
usually needed or environmental changes to become apparent and it may be
impossible to determine whether observed changes will be reversible at somelater point in the uture.
A practicable denition o environmental damage necessitates criteria that are
less prone to the methodological challenges posed by scientic methods. Decision
criteria to evaluate eects o GM crops on biodiversity could be dened using an
approach where GM crop eects are compared to known eects o current agri-
cultural management practices. By putting a relative value on the eects o GM
crops in comparison to known environmental eects o current crop manage-
ment practices, decision criteria would be placed in a context where practical
experiences exist. Provided that this approach is scientically valid and ethically justiable, the approach would allow one to decide whether experienced GM crop
eects are ecologically signicant and why they are judged to be unacceptable.
2.3 Rrh qutin nd g th prjt
Ultimately, any decision by regulators on what they judge being unacceptable
is based on the existing legal rameworks. In addition to considering the actual
legal basis, such decisions are usually taken in a political context that weighs
18
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scientic, ethical and economical criteria with cultural, religious, aesthetic andother relevant social belies and values. Concentrating on environmental impacts
o GM crops on biodiversity, the project addresses both the ecological and the
ethical questions involved in nding an operational approach or the evalua-
tion o environmental damage. The project aims at oering guidance about how
decision-making related to GM crops could be improved to all stakeholders
involved in the process o risk assessment o GM crops (policy-makers, regula-
tory authorities, agricultural biotech companies and scientic expert panels).
The main goals o the project are:
• To identiy the main challenges or regulators when assessing and judgingenvironmental impacts o GM crops including the most important ethical
and ecological knowledge gaps or the interpretation o scientic data
• To analyze types and magnitudes o biodiversity impacts o current crop
management practices and (known) impacts o GM crops on biodiversity
• To perorm a comparative ethical and ecological valuation o impacts
o current crop management practices and impacts o GM crops on
biodiversity
• To develop decision-criteria and guidance or an ethical and ecological
evaluation o impacts o GM crops on biodiversity considering the experi-enced impacts o current crop management practices
2.4 Rtin btwn thi nd gy in th ntxt th givn rrh qutin
Terms such as risk and saety are linked to a conception o damage. The notion
o damage or benet depends on our negative or positive valuation o impacts.
The normative character o the term “damage” implies that both choice and de-
nition o what constitutes a risk are impossible without a value judgment. What
we choose and dene to be a risk is based on a certain normative background.Damage must thereore be dened together with an ethical evaluation as ecolog-
ical analyses alone cannot discover “correct” or “objective” criteria or damage.
Natural sciences can thereby only determine the probability that a certain
impact will occur or the likely consequence i a certain impact has occurred.
Ethics is necessary to clariy the concept o damage in general and the concept
o environmental damage in particular. Both are evaluative concepts reerring to
changes or states o aairs that must be assessed negatively. On the basis o this
conceptual analysis, it becomes possible:
INTRODUCTION 19
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• to critically analyze the appropriateness o legal risk concepts (given that arisk is a unction o probability and extent o damage); and
• to develop scientically sound and intersubjectively acceptable criteria4 or
the valuation o environmental damage that can be shared and accurately
communicated between dierent individuals.
Ecology as a science needs to rely on ethics i it strives to evaluate possible
and real impacts o GM crops on biodiversity because concepts such as damage
or risk, which play a pivotal role in this evaluation, are inherently value-
laden. The evaluation o impacts o GM crops on biodiversity in the contexto current agricultural systems includes both ethical and ecological questions
that need to be claried. From an ecological perspective, or example, not
every environmental impact is o ecological signicance and leading to rele-
vant impacts on biodiversity. From an ethical point o view, not every ecologi-
cally relevant impact on biodiversity is necessarily considered to be morally
wrong. Whether it is wrong or not primarily depends on the importance that
one ascribes to biodiversity. While there is agreement among ethicists that
biodiversity is valuable, there is no agreement on the importance o this value
(compared to other relevant values) and whether it is an inherent or just aninstrumental value.
The outlined research questions necessitate a true interdisciplinary
approach, which, however, includes some challenges. One diculty is that
ecology and ethics use dierent approaches. A challenge in nding an
adequate approach to environmental damage lies in the inherent diculty
to combine the descriptive scientic approach with the normative approach
used in ethics. Natural sciences try to establish the empirical acts o a matter
(what is the case), whereas ethics determine what ought to be the case. Prob-
ably even more challenging is the act that central concepts such as damageor risk are understood in dierent ways by ethicists and ecologists. In the
present project, it took a considerable amount o time to realize that there are
diverging interpretations o these concepts and to agree on common deni-
tions o these concepts. The common understanding now makes it possible
to proceed to the nal phase o this project, concretizing the ethical and
ecological criteria or the evaluation o impacts o GM crops on biodiversity
in a way that will make them applicable or regulators in actual situations o
decision-making.
20
4 Intersubjectively acceptable criteria are normative criteria that a rational person,
that is, a well-inormed person being committed to the best rationale available, would
accept ater a critical assessment. Such criteria are thus inherently universal and
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2.5 Mthd nd pprh th prjt
A particular strength o the project was its ocus on two expert workshops
inviting regulators, members o biosaety committees and scientists with a
background in ethics, ecology and agriculture rom dierent European coun-
tries to combine their eorts in order to create an elaboration o solutions
to the open questions addressed. The project ollowed a stepwise approach
consisting o ve project phases that were centered on the two expert
workshops:
Phase 1: Review and analysis o current knowledge
The rst project phase consisted o an analysis o the relevant scientic litera-
ture to prepare the rst expert workshop that took place in phase 2 o the
project and to select an appropriate method to be used or the group discus-
sions during the workshop. In order to benet the most rom the discus-
sions planned or the rst workshop, the project team decided to make use o
proessional workshop moderation. The moderator team rom Genius GmbH
(Darmstadt, Germany) recommended the use o the Crea-Space method or
the workshop, a method supporting the development o creative potentials inteams and larger groups (El Hachimi and von Schlippe, 2003). The tool is meth-
odologically derived rom Organizational Development and serves to provide a
ramework or the achievement o sel-organization processes. In the context
o the present project, it was deemed to be the ideal tool to eectively introduce
issues derived rom rst results to a constructive discussion level. In order to
avoid a bias towards a predetermined position supported by the project team
workshop, participants were thus not provided with any background documen-
tation prior to the workshop.
Phase 2: First expert workshop: problem identifcation or decision-making
In order to analyze current regulatory decision-making processes, regula-
tors, members o biosaety committees and representatives o the agricultural
biotechnology industry rom dierent European countries were invited to a
rst expert workshop in June 2008. Workshop participants were supplemented
by scientists with a background in ethics, ecology and agronomy (see Annex 1:
List o workshop participants). The aim o the rst workshop was to determine
current approaches and challenges when evaluating scientic data on impacts
INTRODUCTION 21
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o GM crops on biodiversity. The discussion during the group works and in theplenum illustrated that both protection goals and baselines were two consist-
ently emerging issues. Protection goals as specied by existing legislation were
regarded as the exclusive starting point or regulatory authorities or a deni-
tion o damage. Any negative impact on these protection goals would conse-
quently constitute damage. Baselines were recognized as being the crucial
point o any decision-making process o determining what makes a change to
be judged as damage.
Phase 3: Comparative ethical and ecological evaluationPhase 3 aimed at developing solutions or the challenges that had been identi-
ed by invited experts during the rst expert workshop when evaluating impacts
o GM crops on biodiversity. Four approaches were developed to help regulatory
authorities addressing the challenges o vague denitions or both protection
goals and baselines. Prior to the second expert workshop, experts were provided
with our background documents proposing solutions as to how the question o
unclear denitions o both protection goals and baselines could be addressed.
The rst two approaches aimed at enabling a more generic denition o protec-
tion goals in the context o agricultural management. The two latter approachesproposed a methodology or a comparative environmental risk assessment that
can be used to approach the question o an appropriate baseline. For the compar-
ative risk assessment, two currently commercialized GM crops (Bt-maize and
GM herbicide tolerant maize) were used as case studies to specically discuss
the environmental impacts o these GM crops in comparison to current pest and
weed management practices.
Phase 4: Second expert workshop: criteria or evaluation o impacts
o GM crops on biodiversity
The proposed approaches o both the environmental biosaety and the ethics
project parts were presented and discussed during the second expert work-
shop taking place in June 2009 in Engelberg, Switzerland, involving many o the
experts that had attended the rst expert workshop (see Annex 1: List o work-
shop participants). The background documents elaborated during phase 3 o
the project were critically discussed with all participating experts during
the group works taking place in the second workshop. All documents were
not meant to be conclusive as experts were invited to provide eedback and
22
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criticism to the approaches proposed. The background documents werediscussed in our group works to determine both strengths and weaknesses o
the our proposed approaches:
• Group work 1: Ethical reerence system to assess biodiversity
• Group work 2: Operational denition o protection goals
• Group work 3: Comparative environmental risk assessment Bt-maize
• Group work 4: Comparative environmental risk assessment GMHT maize
For each group work, participants were randomly grouped into three
working groups. In each group, a rapporteur took notes on the main results o the discussion and presented the results in a short presentation to the plenum
in a plenary session ollowing the group work.
Phase 5: Synthesis of workshop results – preparation of guidance document
During the last step o the project, results and eedback obtained during the
second workshop were used to elaborate a synthesis o the relevant ethical
and ecological aspects when evaluating impacts o GM crops on biodiversity.
The results o the our group works and the eedback collected by experts were
used to improve the approaches proposed (see sections 8 – 9). The project results were revised and compiled into a guidance document that can be used or an
inormed decision-making process or the evaluation o impacts o GM crops
on biodiversity. The guidance document summarizes criteria to assist decision-
making on the relevance o impacts o GM crops on biodiversity.
2.6 outin th rprt
The rst part o the report contains an executive summary (chapter 1), a general
introduction (chapter 2) and a general denition o the term damage (chapter 3)that is mainly infuenced by ethical considerations.
The second part o the report (chapters 4 – 8), which was written by Agro-
scope ART, is primarily dealing with the ecological conception o environ-
mental damage:
Chapter 4 presents the general denition o the term “biodiversity,” intro-
duces the dierent components o biodiversity and discusses the diverse moti-
vations to preserve biodiversity. Moreover, environmental protection goals
as specied by Swiss legislation are described with regard to agriculture in
INTRODUCTION 23
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general and more specically in view o the use o genetic engineering. Finally,the ecological relevance o biodiversity is discussed or species and habitat
diversity and or ecosystem unctions.
Chapter 5 presents an approach as to how operational protection goals or the
evaluation o impacts o GM crops on biodiversity could be dened. A matrix is
introduced that lists all entities o biodiversity that require protection. The matrix
lists actors that need to be considered when dening corresponding assessment
and measurement endpoints. It is stressed that clearly dened endpoints are
necessary or regulatory decision-making as they speciy what deserves protec-
tion. It is recommended that one dene indicators and parameters that can bemeasured to determine whether harm to the protection goals specied occurred.
Chapter 6 discusses the issue o using thresholds in environmental deci-
sion-making. It is recognized that the legal rameworks regulating the use o
GMOs operate according to the thresholds-concept (i.e., risks are acceptable as
long as they do not exceed a certain specied threshold). It is nevertheless also
emphasized that regulatory authorities do not provide clear threshold values,
which challenges decision-making processes.
Chapter 7 discusses how a baseline or the comparison o dierent agri-
cultural management practices could be dened to determine whether thecultivation o GM crops is better, equal or worse than current practices. Pest
management in maize is used as a case study to compare dierent GM and
non-GM based cropping systems. It is concluded that it is impossible to per-
orm a generic comparison o dierent pest management practices, mainly
because these are regulated based on dierent legal rameworks. Instead, an
approach is proposed that allows dierentiating between intended and unin-
tended eects o the pest management practice applied. The proposed fow
chart can urther be used to determine which type o unintended eects may
represent environmental damage.Chapter 8 uses the eects o dierent weed management practices in maize
to discuss how one can cope with rather vaguely denable damages on arm-
land biodiversity that might occur rom changes in agricultural management
practices. Since long time periods may elapse beore these damages become
apparent, appropriate risk management options might be a valuable option to
Reduce the risks o these damages occurring.
The third part o the report (chapter 9), which was presented by Ethik im
Diskurs, discusses the topic rom the ethical point o view.
24
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Chapter 9 introduces the ethical reerence system (ERS) as a useul toolor regulatory decision-making that allows speciying and justiying plausible
ethical criteria or the evaluation o environmental impacts o GM crops on
biodiversity. It is emphasized that the ERS provides regulators with a general
orientation grid by describing the dierent ethical theories that may underlie
the protection o biodiversity. The ERS helps to determine which ethical
position one intuitively avors and acilitates a more refected understanding o
the ethical views enshrined in the law.
The report ends with a chapter summarizing general recommendations to
decision-makers (chapter 10)Finally, Annex 2, which was presented by Ethik im Diskurs, character-
izes the term “risk” and discusses it rom a general point o view, and more
specically in the context o the given research questions. Although the report
mainly ocuses on the question as to how one can nd criteria to determine
what constitutes environmental damage, the term “risk” is a recurring topic
when discussing denitions o damage. Under certain circumstances (e.g., i
it is dicult to clearly characterize which impacts constitutes damage),
relying on risk mitigation measures may be an adequate measure to approach
this question.
INTRODUCTION 25
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a GeNeRal DeINITIoN
o DaMaGe
CHAPTER 3
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28
3 a GeNeRal DeINITIoN o DaMaGe
In everyday language, something is called damage or harm i state S2 repre-sents a change that is valued negatively compared to an initial state S1. I, or
instance, a house burns to the ground and its inhabitants lose their belongings,
or i a healthy person alls ill and suers rom the illness, this is called damage
or harm. It is important to realize that damage is an evaluative notion, even
though the evaluation is based on the establishment o acts. For this reason,
there can be no value-ree scientic risk assessment. Science can ascertain
the actual state o something and it can describe and explain changes and its
related ecological implications. However, science can only answer the ques-
tion rom a scientic perspective as to how this state or these changes shouldbe evaluated.
To be more exact, damage as an evaluative notion does not denote a
change that is evaluated negatively, but a change that ought to be evaluated
negatively. In order to determine whether a state or an event is damage, we
need a reerence system. The purpose o this system is to name the values
or goods that allow justied negative evaluations o changes. These may be
“zero values” such as reedom rom pain and suering (whereby the negative
change essential or damage would be the occurrence o pain and suering)
or positive values such as pleasure, beauty, bodily integrity or lie (in the senseo being alive).
The evaluative dimension o the notion o damage consists o two aspects.
On the one hand, suering damage is always bad or the individuals (entities)
aected. That is the prudential dimension which reers to what is good or bad
or an individual living organism. On the other hand, damage is usually some-
thing that should not to be inficted on others or something the others should
be protected rom. This is the ethical dimension. It is also the normative basis o
the legal understanding o damage.
From an ethical point o view, damage is not necessarily bad or repre-hensible. Rather, damage is either neutral or relevant. “Neutral” means that
nobody can be held responsible or it. A congenital disease, or instance,
may damage the aected child, even though it is the unpredictable result o
a natural genetic process. “Relevant” means that the damage is to be evalu-
ated negatively or positively in a moral sense. I the evaluation is negative, the
infiction o damage is morally inadmissible; i it is positive, the infiction is
morally admissible or even required. The latter is the case, or example, when
a teacher gives a student a bad grade. This may damage the student: she may
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A GENERAL DEFINITION OF DAMAGE 29
eel bad or have to repeat a course. However, i the grade is adequate to herperormance, the infiction o damage is morally justied. On the other hand,
torturing someone just or the un o it implies inficting a kind o damage that
is morally prohibited.
What kind o entities can be damaged? In everyday language, there are
dierent kinds o damage: economic damage, political damage, environmental
damage, damage to persons, animals, plants or engines, construction damage,
re damage – to name just a ew. These damages can be roughly classied into
three main groups: systemic damage, unctional damage and damage o indi-
vidual beings. Environmental damages, or instance, are systemic damages,engine damage is a unctional damage and damage to persons is a damage o an
individual being (a person).
I we were to undertake a thorough and comprehensive conceptual analysis
o the notion o damage, the ollowing questions would have to be answered:
• Can there be systemic damages? Is it plausible to assume, or instance, that an
ecosystem as such is damaged i its homeostatic equilibrium is disrupted?
• Can a loss o biodiversity as such be damage?
• Can plants or any other nonsentient living beings be damaged as such?
• Can nonliving entities (a car) or parts thereo (a car engine) be damagedas such?
In order to answer these questions, one would have to clariy what condi-
tions must be met or the correct application o the notion o damage. This
would be tantamount to an ontological analysis o the conditions o damage.
The main questions to be tackled would be:
• Can nonexisting entities (or instance, dead persons) be damaged as such?
• I only existing entities can be damaged as such, what is an existing entity?
• I something exists only nominally, that is, as an abstract entity (such as, orexample, an ecosystem), can it be damaged as such?
• Does damage presuppose the ability o experiencing it?
This analysis o the general notion o damage would be necessary beore
proceeding to the analysis o the specic notion o environmental damage.
Unortunately, most analyses perormed by ecologists and ethicists do not
ollow this two step procedure. This is why their discussion o this topic is
rather unsatisactory.5
5 One would be able to show that none o the conceptions or criteria o ecological
damage that play a role in this discussion, especially with regard to GMOs – such as,
evolutionary integrity, selective advantage, natural variation, similarity, impairment
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cHaRacTeRIZING THe PRoTecTIoN
Goal “BIoDIVeRsITY”
CHAPTER 4
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34
4 cHaRacTeRIZING THe PRoTecTIoN Goal “BIoDIVeRsITY”
4.1 Bkgrund
Protection goals as specied by existing legislation are the exclusive starting point
or regulators or a denition o damage related to the evaluation o GM crops.
Typically, legal rameworks make relatively vague specications on the question
regarding what it is to be protected rom harm resulting rom human activities. Both
rom an ethical and ecological point o view, the legislative terms used to describe
the protection goals “environment” and “biodiversity” are however too vague to be
scientically assessed. The use o criteria to evaluate damage necessitates nding
an operational way o how to characterize the protection goal “biodiversity.” Ina rst step, the term “biodiversity” is thus examined more closely, ollowed by a
discussion o the environmental protection goals as specied by Swiss legisla-
tion both rom a general point o view and more specically in relation to the use
o genetic engineering. Finally, a proposal is made as to how the protection goal
“biodiversity” in agricultural landscapes could be operationally dened.
4.2 Wht i bidivrity?
4.2.1 Gnr dinitinAlthough the term biological diversity – or biodiversity – has been extensively
used in the past decades, the underlying concepts and denitions are anything but
uniorm. Probably one o the most prevalent denitions is given by the Conven-
tion on Biological Diversity (CBD) stating “Biological diversity means the vari-
ability among living organisms from all sources including (…) terrestrial, marine
and other aquatic ecosystems and the ecological complexes of which they are part;
this includes diversity within species, between species and of ecosystems” (CBD,
1992). As such, biodiversity is essentially an abstract concept, albeit one o which
most would say that they have some intuitive understanding. Biodiversity is otentermed as the variety o lie on earth and the natural pattern it orms (CBD, 2000).
The range o possible interpretations o such a conception o biodiversity is not
simply wide, but it is so wide that it becomes exceedingly dicult to comprehend
(Gaston, 1996). As a consequence, the concept o biodiversity is imprecise and it
risks being dened so broadly that it equates to the whole o biology. Unortu-
nately, a denition treating biodiversity as more or less all living things on earth
is o little use to policy-making where alternatives have to be selected in light o
given conditions to guide and determine present and uture decisions.
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CHARACTERIZING THE PROTECTION GOAL “BIODIVERSITY” 35
4.2.2 Ditinguihing btwn dirnt mpnnt bidivrity A number o schemes have been proposed to distinguish the major eatures o
biodiversity and to better characterize what constitutes the “variety o lie.” A more
specic denition is given by Redord and Richter (Redord and Richter, 1999),
dening biodiversity as “the variety of living organisms, the ecological complexes in
which they occur, and the ways in which they interact with each other and the phys-
ical environment.” The authors propose to dene biodiversity in terms o dierent
components – genetic, population / species and ecosystems – each o which has
compositional (the identity and variety o elements), structural (the physical
organization or pattern o elements) and unctional attributes (ecological andevolutionary processes). The three latter attributes reer to an approach initially
suggested by Noss (Noss, 1990) to characterize biodiversity in terms o ecological
processes recognizing that biodiversity is not simply the number o genes, species,
ecosystems or any other groups o things in a dened area (as dened by the (CBD,
1992). Although such a scheme may be helpul in acilitating a practicable approach
to rening the concept o biodiversity, one has to recognize that even the rened
concept (Table 1) has its operational limits. Many o the terms used to describe
the dierent attributes o biodiversity are still too broad to be eectively used in a
decision-making process that aims at quantiying biodiversity changes.
4.2.3 Mtivtin t prrv bidivrity
The primary motivation to preserve biodiversity is oten purely in the sel-interest
o mankind (CBD, 2000). The global loss o biodiversity is said to threaten ood
supply, the source o wood, medicine, energy and essential ecological unctions
as well as opportunities or recreation and tourism.
The Secretariat o the CBD lists a vast number o “goods and services”
provided by ecosystems:
• Provision o ood, uel and ber • Providing o shelter and building material
• Purication o air and water
• Detoxication and decomposition o wastes
• Stabilization and moderation o Earth’s climate
• Moderation o foods, droughts, temperature extremes and the orces o wind
• Generation and renewal o soil ertility including nutrient cycling
• Pollination o plants including many crops
• Control o pests and diseases
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36
• Maintenance o genetic resources as key inputs to crop varieties and live-
stock breeds, medicines and other products • Cultural and aesthetic benets
• Ability to adapt to change
Today, ecosystem services are usually described according to the deni-
tion given by the Millennium Ecosystem Assessment (Millennium Ecosystem
Assessment, 2005; EASAC, 2009). Ecosystem services are thereby dened as
the benets people obtain rom ecosystems and they are categorized into our
broad categories:
Table 1: Concept o the term “biodiversity” according to its three main components and the
corresponding attributes (based on Noss, 1990; Kaennel, 1998; Redord and Richter, 1999).
Gnti divrity
Phenotypic diversity
Variety, cultivar
Subspecies
Genetic structure
Gene fow
Genetic processes
spi divrity
Species richness
Species abundance
Species evenness
Species density
Endangered species
Threatened species
Population structure
Surrogate species
Indicator species
Keystone species
Flagship species
Umbrella species
eytm divrity
α, β, γ-diversity
Landscape types
Communities
Ecosystems
Landscape patterns
Habitat structure
Landscape processes
Land-use trends
Ecosystem processes /
services
Parasitism, predation
Pollination
Soil processes
Nutrient cycles (C, N, P, S)
Biomass production
cmpitin
(Identity and variety
o elements)
strutur
(Physical organization,
pattern o elements)
funtin
(Ecological and
evolutionary processes)
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CHARACTERIZING THE PROTECTION GOAL “BIODIVERSITY” 37
• Supporting services, which provide the basic inrastructure o lie, includingthe capture o energy rom the sun, the ormation and maintenance o soils
or plant growth and the cycling o water and nutrients (these services
underlie all other categories).
• Regulating services, which maintain an environment assisting human
society, managing the climate, pollution and natural hazards such as disease,
food and re.
• Provisioning services providing the products on which lie depends (ood,
water, energy) and the materials that human society uses or ashioning its
own products. • Cultural services providing landscapes and organisms that have signicance
or humankind because o religious or spiritual meanings they contain or
simply because people nd them attractive.
The need to preserve biodiversity is moreover oten linked to dierent
obligations (Kunin and Lawton, 1996; SCNAT, 2006):
• Moral and ethical obligations: biodiversity represents a heritage that has to
be preserved or uture generations.
• Human well-being: many organisms (fowers, birds, butterfies) bringpleasure to many people and enrich their lives. Biodiversity is urthermore
important or personal recreation and regeneration as people enjoy and
relax in a natural, diverse environment.
• Insurance: biodiversity can be useul as a potential resource or survival
in a changing environment by providing new drugs, ood stus or genetic
resources or crops and arm animals.
• Ecosystem services: organisms provide essential services maintaining the
lie-support systems o the planet (see above).
• Economy: biological resources are the pillars upon which human civiliza-tions are built as they support such diverse industrial sectors as agriculture,
pharmaceuticals, construction, waste treatment and tourism.
• Preservation o the homeland (“Heimat”): Species and habitats in a particular
country constitute an important part o the homeland and create identity.
Most people would certainly agree that a number o the mentioned obli-
gations are justied, but there are inevitably also debates on the question
whether all o these obligations are valid and which are to be preerred over
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others. However, such a discussion opens up a vast number o topics that arenot relevant or the ultimate purpose o the present report. Discussing the
dierent value positions relevant to the dierent motivations and determining
which are ethically relevant and deendable is thereore beyond the scope o
this report. The presented Lists are thereore to be seen as an unranked list
o values that shape the discourse about policy goals when trying to nd an
operational denition o biodiversity (see section 5).
4.3 envirnmnt prttin g piid by swi gitin
4.3.1 Gnr nvirnmnt prttin g rtd t bidivrity
In Switzerland, the protection o biodiversity is laid down in a number o
national legislations based on international environmental treaties6 and on the
Swiss Federal Constitution. The overall environmental policy goal is thereby
to preserve and to promote native species and their habitats. The legislation is
complemented by a number o enactments o the Swiss Federal Council that
have a binding status or the ederal authorities such as the “Landschatskonzept
Schweiz” (landscape concept Switzerland) (Buwal, 1999). Therein, a number o
more detailed environmental policy goals are specied. In general, anthropogenicinfuences on the environment should not lead to additional Red List species and
to a reduction o widespread species. Moreover, threatened species and their
habitats should be preserved, their conservation status should not decrease and
the number o Red List species should diminish yearly by 1%. Detailed lists o
protected species and habitats are listed in respective legal texts (NHG, SR 451;
NHV, SR 451.1).7
4.3.2 envirnmnt prttin g rtd t griutur
According to the Swiss Federal Constitution, agriculture has our main goals: (1)to assure the provisioning o the population, (2) to preserve the natural resources
on which lie depends, (3) to maintain cultural landscapes and (4) to support a
decentralized settlement o the country. In order to achieve these policy goals,
the Federal Oce or the Environment (FOEN) and the Federal Oce or Agri-
culture (FOAG) specied a number o environmental policy goals or the agricul-
tural sector. The policy goals are dened based on current legal requirements as
6 Such as the Convention on Biological Diversity, the Convention on the Conservation
o European Wildlie and Natural Habitats and the International Treaty on Plant
Genetic Resources or Food and Agriculture
7 Similar legal texts exist in the European Union, e.g., the Council Directive 92/42/EEC
o 21May 1992 on the conservation o natural habitats and o wild auna and fora
(European Commission 1992)
38
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laid down in various acts, ordinances, international treaties and decisions o theSwiss Federal Council (Bau/BLW, 2008). Based on these premises, agriculture
has to contribute substantially to the conservation and promotion o biodiversity.
Biodiversity is thereby classied into three main aspects: (1) species and habitat
diversity, (2) genetic diversity within species and (3) unctional biodiversity.
4.3.2.1 Species and habitat diversity
An important policy goal o Swiss agriculture is to preserve and promote native
species that are typical or agricultural landscapes (i.e., species that mainly
occur on agricultural land or depend on agricultural use). The environmentalpolicy goals or agriculture give very precise indications on which species
and habitat deserve protection within agricultural landscapes as two types
o species groups are specied deserving special considerations: (1) target
species are locally or regionally occurring species that should be preserved
and promoted as they are threatened on a national level. In addition, Swit-
zerland carries particular responsibility within Europe or the conservation
o these species, while (2) character species are characteristic or a particular
region and they are representative or a specic habitat (i.e., they serve as an
indicator or quality o the habitat they occur in). The environmental policy goals or agriculture moreover provide detailed species lists or both target and
character species that were elaborated by a working group involving multiple
stakeholders rom agriculture and nature conservation (Bau/BLW, 2008). The
lists cover a large number o taxa that deserve special consideration. The aunal
taxa include mammals, birds, reptiles, amphibian, beetles, bees, butterfies, lace-
wings, dragonfies, grasshoppers and mollusca, while the foral taxa consist o
fowering plants, erns, mosses, lichens and ungi. The report urther species a
number o habitats that should be preserved and promoted as they are typical
or agricultural land uses (e.g., ecological compensation areas, meadows andpastures, hedgerows, ruderal areas etc). Given that the character species listed
are representative or a wide range o these habitats, the approach combines
the conservation o species and habitat diversity.
4.3.2.2 Genetic diversity within species
Genetic diversity is a prerequisite or the long-term survival o wild species.
The Swiss environmental policy goals or agriculture demand the preserva-
tion o genetic diversity o the species and habitats that are to be protected as
CHARACTERIZING THE PROTECTION GOAL “BIODIVERSITY” 39
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set out above. In addition, the national action plan on the conservation andsustainable use o plant genetic resources or ood and agriculture aims at
preserving a broad genetic diversity o the crop plants present in Switzerland
and their wild relatives in view o ood production and security. Plant genetic
resources are the starting point or any plant breeding program that aims at
developing tailor-made varieties or uture needs. Apart rom economic bene-
ts, plant genetic resources also have ecological value (e.g., by being adapted
to local conditions such as being resistant to plant diseases) and cultural value
(e.g., by representing traditional regional production).
4.3.2.3 Functional biodiversity
According to the Swiss environmental policy goals or agriculture, agricultural
production has to preserve the ecosystem services provided by biodiversity. The
part o the biosphere providing the desired ecosystem services is termed “unc-
tional biodiversity.” Human society obtains a wide array o important benets
rom biodiversity and associated ecosystems. These ecosystem services are
essential to human well-being and to sustaining lie on earth since these serv-
ices operate on such a large scale, and in such complex ways, that most services
could not be replaced by technology (Daily, 1999; CBD, 2000; Daily et al., 2000).Functional biodiversity covers ecosystem services such as soil ertility, natural
pest regulation and pollination by insects (see section 4.2.3). The economic value
o 17 ecosystem services or the entire biosphere has been estimated to $33
trillion per year (Costanza et al., 1997). The production o 84% o crop species
cultivated in Europe, or example, directly depends on insect pollinators, espe-
cially bees (Gallai et al., 2009), while predators and parasitoids ulll relevant
ecological unctions by contributing to the natural regulation o arthropod pest
populations within crop elds in agricultural landscapes. The total economic
value o pollination worldwide is estimated to amount to €153 billion, whichrepresented 9.5% o the value o the world agricultural production used or
human ood in 2005 (Gallai et al., 2009). The value o natural pest control attrib-
utable to insects in the United States is estimated to be US $4.5 billion annually
(Losey and Vaughan, 2006).
4.3.2.4 Programs to assess Swiss environmental policy goals or agriculture
To determine whether the current Swiss environmental policy goals or agricul-
ture are met, there is a need or programs assessing the status o the dierent
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components o biodiversity. The status o implementation o these programs varies considerably among the dierent components o biodiversity. Several
programs are running that assess the state o species and habitat diversity
in Switzerland. Instruments assessing species and habitat diversity include
among others the Red List species, the Biodiversity Monitoring Switzerland
(BDM, 2009), and the Swiss Bird Index (Keller et al., 2008). These instruments
assess a number o dierent indicators and allow one to obtain a relatively
good estimation o the state o species diversity and to a lesser extent o habitat
diversity. Only a ew activities have been started or genetic diversity. Genetic
diversity is primarily collected and inventoried or arable crops, vegetables,ruit trees and or orage grasses as part o the national action plan on the
conservation and sustainable use o plant genetic resources or ood and agri-
culture. Although not yet collected, there are plans to inventory the genetic
diversity o wild plants that are relatives o crop plants and or wild plants used
or medicinal purposes or as ornamental plants (Häner and Schierscher, 2009).
No inormation is currently available on the state o unctional biodiversity as
no programs or its assessment are implemented.
4.3.3 spii prttin g rtd t gnti nginring In Switzerland, the use o genetic engineering is regulated on the constitutional
level (BV, SR 101). According to Article 120 BV, humans and their environment
shall be protected against the misuse o genetic engineering. The rationale
or this specic regulation is ounded on the novelty o the technology and
the uncertainties related to the consequences o the transormation process
o genetically modied organisms (GMOs). The Swiss Federal Law relating to
Nonhuman Gene Technology specically prescribes the protection o humans,
animals and the environment rom abuses o genetic engineering (GTG, SR
814.91). In particular, the law mandates that GMOs intended or use in theenvironment may only be marketed i experiments in contained systems or
eld trials have shown that they: (a) do not impair the population o protected
organisms or organisms that are important or the ecosystem in question; (b) do
not lead to the unintended extinction o a species o organism; (c) do not cause
severe or permanent impairment o nutrient fows; (d) do not cause severe or
permanent impairment o any important unctions o the ecosystem in ques-
tion, in particular the ertility o the soil; and (e) do not disperse, or rather, their
traits do not spread in an undesired way.
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4.4 Th gi rvn bidivrity
4.4.1 spi nd hbitt divrity
Species richness is oten used as a surrogate or overall biodiversity even though
the nature and identication o species continues to be controversial, though
no one thinks that species richness is all there is to biodiversity (Maclaurin and
Sterelny, 2008). Habitats with a high species richness are requently regarded
as being more valuable than habitats with a lower species richness. However,
species richness is not always an appropriate indicator or the ecological value
o habitats as the habitat type plays an important role in the evaluation. Gener-ally spoken, species-poor habitats oten contain common, widespread species,
whereas species-rich habitats are more likely to contain rare and threatened
species. Yet, some habitats such as moorland are characterized by being inher-
ently species poor and by containing particularly adapted, rare species. Certain
disturbances, such as increased nutrient inputs, might lead to a local increase in
biodiversity in these habitats due to the invasion o less specialized and more
widespread species that would not be able to survive in the originally nutrient-
poor environment. As the invading species are generally more competitive,
they usually replace the initial, rare species that can typically be ound in thisparticular habitat type. From a nature conservation point o view, the increased
biodiversity ound in these typical habitats is not desired as the specialized, rare
species represent a particularly valuable component o biodiversity (Duelli, 1994;
Kägi et al., 2002). Similarly, recent results o the Swiss Biodiversity Monitoring
showed a slight increase in species richness in meadows when compared to the
rst assessment in 2001 (BDM, 2009). However, the analyses also showed that the
increase was mainly due to the occurrence o widespread and generalist species
already present in intensively managed, nutrient rich meadows. The net increase
in species richness was thus not particularly valued as rare and specialist speciescharacteristic or agricultural landscapes were missing.
Further examples show that increases in species richness are not always
regarded as a positive development rom a nature conservation point o view.
Despite a global perception o declining biodiversity, managers are requently
presented with situations where biodiversity is increasing due to the arrival o
invasive species (Thompson and Starzomski, 2007). Invasions by alien species
are however regarded as being one o the major direct causes o biodiversity
loss (among other actors such as land use change, pollution, unsustainable
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natural resources use and climate change) (Slingenberg et al., 2009). Losseso native species may not result in net changes in biodiversity i exotic species
move into an area and replace them. To the public and conservation managers,
however, the loss o particular, valued native species is o concern, more so than
the net change in biodiversity (Thompson and Starzomski, 2007).
4.4.2 eytm untin nd pi divrity
Rationales or the protection o biodiversity are oten based on the argument
that species provide ecological goods and services that are essential or human
welare. Some consensus appears to be crystallizing on the overall signicanceo maintaining ecosystem integrity and unction (Gaston, 1996). This puts more
emphasis to ecological processes than is immediately evident rom many deni-
tions o biodiversity, or example, the one put orward by the CBD (CBD, 1992)
that does not encompass unctional diversity enabling most ecosystem services.
The preservation o unctional diversity also necessitates other conservation
strategies than would be the case i primarily individual species would have to
be preserved. One o the central questions in ecology is thereore how biodiver-
sity relates to ecological unctions. Several hypotheses have been ormulated to
describe the relationship between ecosystem unctions and species diversity: • Diversity-stability hypothesis (Macarthur, 1955; Elton, 1958): Early theo-
ries established the axiom that diverse ecological communities are the most
stable. The rate o ecosystem processes is highest with the greatest number
o species. As the number o species in the system increases, the ability to
recover rom disturbances is higher.
• Rivet hypothesis (Ehrlich and Ehrlich, 1981): The rivet hypothesis assumes
that the loss o species has an increasingly critical eect on the unction o
an ecosystem. All species are equally important in maintaining the system’s
stability and every species has an equal and additive eect on unction. Whilethe eect o the loss o one species may be relatively small, the loss o several
species can lead to the complete collapse o the unctioning ecosystem.
• Redundancy hypothesis (Walker, 1992): This hypothesis predicts that not
all species are o concern as some are redundant. A loss o species rich-
ness may be o little consequence to ecosystem unctioning because unc-
tional groups comprise many dierent species. Losing most species may
have little eect, but the loss o some species may result in a dramatic
destabilization o the system.
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• Idiosyncratic hypothesis (Lawton, 1994): This hypothesis suggests that thereis no clear relationship between species number and ecosystem unctions
since the contribution o species to unction is unpredictable as both the
identity and order o species loss will aect unction dierentially. Ecosystem
unction changes when diversity changes, but the magnitude and direction
o change are unpredictable as the roles o individual species are complex
and varied.
• Insurance hypothesis (McNaughton, 1977; Naeem and Li, 1997): According
to this hypothesis, biodiversity insures ecosystems against declines in their
unctioning. More diverse ecosystems are more likely to contain some speciesthat can withstand perturbations and thus compensate or unctional loss o
other species being reduced or eliminated by the perturbation.
There is rather little scientic evidence rom experimental studies
supporting both the diversity-stability hypothesis and the rivet hypothesis.
Evidence in support o a linear dependence o ecosystem unction on diver-
sity (i.e., that even rare species contribute to unction) is practically nonex-
istent (Schwartz et al., 2000). There is nevertheless convincing evidence that
species-rich systems deliver ecosystem services more reliably than species-poor ones. Empirical data suggests that the ecological stability is generated
more by a diversity o unctional groups than by species richness, which
supports the insurance hypothesis (Peterson et al., 1998). Ecosystem serv-
ices typically do not depend on the presence o specic species, especially
not rare, narrowly distributed species (Maclaurin and Sterelny, 2008). At
least among species within the same trophic level, rarer species are likely
to have small eects. Species are thus not o equal importance to ecosystem
services and species richness per se is not necessarily a key element o
ecosystem unctioning. Moreover, landscape complexity may compensateor biodiversity loss because o local management intensity. The diversity o
arable weeds, or example, is higher in organic than in conventional elds,
but only in simple landscapes, as landscape diversity enhances species diver-
sity in conventional elds to a similar diversity level (Roschewitz et al., 2005).
In contrast to what may be expected, introducing diverse habitats (and less
intensive practices such as organic arming) has only a great eect in simple
landscapes and will positively infuence resilience (i.e., the capacity to main-
tain ecosystem services ater disturbance), whereas complex landscapes are
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already characterized by a high biodiversity sustaining ecosystem services(Tscharntke et al., 2005). Negative impacts o intensive arming such as herbi-
cide applications only occur in simple landscapes where colonization o arable
weeds rom the surrounding is limited, whereas complex landscapes appear to
mitigate local anthropogenic weed elimination.
Hence, ecosystem properties may be insensitive to species loss as (i)
ecosystems may have multiple species carrying out similar unctional
roles, (ii) some species may contribute relatively little to ecosystem prop-
erties, or (iii) properties may be primarily controlled by abiotic environ-
mental conditions (e.g., weather events) (Hooper et al., 2005). The mostdramatic changes in ecosystem services are likely to come rom altered
unctional compositions o communities and rom the loss (within the
same trophic level) o locally abundant species rather than rom the loss
o already rare species (Diaz et al., 2006). Interestingly, most conservation
eorts concentrate on rare species. Rare species, however, may not interact
strongly with other species in the ecosystem, nor be able to replace the eect
o a dominant species. In conservation terms, it is more crucial to identiy
which species are likely to have disproportionate eect i they are lost. Espe-
cially in agroecosystems, species richness is oten less important or ecosystemunctions than the presence o a small subset o species (Shennan, 2008).
High diversity o unctional groups may allow reorganizations ater distur-
bances due to a higher number o insurance species. Agricultural landscapes
must be a mosaic o well connected early and late successional habitats to
support a high biodiversity and thereby the capacity to recover rom minor
and major small- and large-scale disturbances (Tscharntke et al., 2005). From
an ecosystem service conservation perspective, it is thus more important to
protect species which have no unctional equivalent and to maintain diver-
sity within unctional groups than to ocus on conserving particular individualspecies (Thompson and Starzomski, 2007).
4.4.3 summry th gi rvn bidivrity
In the ollowing, we will argue that there are two main motivations or the
conservation o biodiversity: (1) the protection o rare and threatened species
and (2) the unctioning o ecosystem services based on genetic and species diver-
sity (ecological resilience). Genetic diversity (i.e., biodiversity within species) is
thereby crucial to a species’ ability to adapt to its environment. An important
CHARACTERIZING THE PROTECTION GOAL “BIODIVERSITY” 45
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oPeRaTIoNal DeINITIoN
o PRoTecTIoN Goals
CHAPTER 5
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50
5 oPeRaTIoNal DeINITIoN o PRoTecTIoN Goals
5.1 Diiuty t ind n unmbiguu dinitin th trm bidivrity
One o the goals o the present study is to obtain a practicable conception o biodi-
versity that can be used to describe the agricultural context prevalent in Swit-
zerland. Scientically, the term “biodiversity” can be dierentiated into dierent
components (genetic, species and habitat diversity) and into dierent attributes
such as composition, structure and unction (see section 4.2). Although the scien-
tic classication provides a more precise denition o biodiversity, the rene-
ment also substantially broadens the conception o biodiversity without acili-
tating its operational use in decision-making. Despite its multiple dimensions,biodiversity is usually equated with species richness only (Feld et al., 2009). Not
surprisingly, the unctional, structural and genetic components o biodiversity
are still poorly addressed. This may, to a certain extent, be due to scientic limita-
tions o nding appropriate indicators or these components, but also refects the
act that biodiversity assessment and monitoring until recently has been mainly
driven by conservation biologist. This becomes apparent when looking at the
programs implemented in Switzerland to assess biodiversity (see section 4.3.2).
The biodiversity components most oten measured today are species richness
and habitat diversity, while genetic diversity is primarily covered by assessingthe number o livestock breeds and crop varieties (BDM, 2009). Moreover, there
are literally no routine monitoring programs that assess ecosystem services or
ecosystem unctions.
I even a rened concept o biodiversity (see Table 1) remains dicult to
apply in practice, how can the concept then be made operational to support policy
decisions? The variety o dierent denitions shows that biodiversity cannot be
dened as a clearly measurable quantity, that is, it is impossible to provide an
index allowing to rate ecosystems or collections o entities according to their
degree o diversity (Norton, 2008). One has to recognize that it is probably simi-larly impossible to nd an unambiguous scientic denition o the term biodi-
versity. The goal should thus be to nd an approach that enables stakeholders
agreeing upon the way orward. The denition must allow one to nd a common
language that allows communication about what deserves protection because
it is specically valued. As with other metaconcepts, such as, sustainability or
ecosystem health, biodiversity achieves operative sense only when it is clearly
dened and used as a means to inorm specic management decisions in specic
ecosystems using specic indicators (Failing and Gregory, 2003).
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OPERATIONAL DEFINITION OF PROTECTION GOALS 51
Focusing on the management context necessitates going beyond generaldenitions to set scale and context-specic management objectives. At this stage,
managers (i.e., regulatory authorities) need to deal with the dicult question o
what is desired. Ultimately, policy decisions on what is to be protected are based on
the legal rameworks regulating the conservation o biodiversity (see section 4.3).
Nevertheless, policy decisions are inevitably linked to practical and nancial
constraints, making it impossible to conserve all components o biodiversity in
the same manner or in the way it would be desired. The protection o biodiversity,
as laid down in the legislation, is a man-made concept refecting social values.
When thinking about an apparently scientic concept such as biodiversity, oneis orced to conclude that the concept remains ambiguous until it is clear what
society is caring about (Norton, 2008). One could thus argue that a policy-rele-
vant denition has to be guided by both social and scientic criteria as what
deserves protection is also dened by what people care about. Determining
what truly deserves protection will thus inevitably be based on the motivations
or biodiversity conservation, on the relevance that is given to biodiversity to
serve these motivations (see section 4.2.3) and on the implicit values under-
lying the protection o biodiversity (see Box 2). Science and empirical evidence
can thereby guide the discourse about policy goals and indicate what ecologicaltheories tell us about the relevance o biodiversity (see section 4.4).
5.2 a mtrix r n prtin dinitin bidivrity in griutur ndp
Protection goals, as laid down in the existing legal rameworks, are usually
described too vaguely to be scientically assessed and to support regulatory
decisionmaking. In the ollowing, a matrix or an operational denition o protec-
tion goals is proposed that consists o a three-step process speciying protection
goals, assessment endpoints and measurement endpoints (Table 2). The rst twosteps allow a more explicit characterization o the protection goal “biodiversity
in agricultural landscapes” by speciying a number o assessment endpoints
that describe the entities deserving protection in more detail. In the third step,
measurement endpoints are dened that represent a measurable ecological
characteristic, which can be related to the assessment endpoint chosen. The
matrix presented herein will not be able to deliver a denite answer to the chal-
lenge o dening ully operational protection goals. The matrix should rather
be seen as a tool that supports an operational denition o biodiversity. A true
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52
operational denition o protection goals will need to be elaborated in a trans-parent process involving all relevant stakeholders (regulators, applicants and
scientists) (see section 5.3). The matrix is urthermore not restricted to GM plants
and may thus orm the basis or any evaluation o environmental impacts on
biodiversity in agricultural landscapes.
5.2.1 Dinitin prttin g
The rst step or the denition o protection goals aims at identiying the dierent
areas o protection to be considered as laid down in existing legal rameworks.
The area o protection has been divided into the two principal categories, that is,“biodiversity conservation” and “ecosystem services” (Table 2). Biodiversity conser-
vation covers red list species and species o high conservation or cultural value
rom a range o dierent taxa including mammals, birds, amphibians, insects (such
as butterfies) and plants. In addition to species diversity, biodiversity conservation
also involves protected habitats and landscapes.
Protection in this category primarily ocuses on habitats as the term “land-
scape” is oten less clearly dened and habitats are the units usually listed in the
legislation (European Commission, 1992; NHV, SR 451.1). The operational deni-
tion o these two categories will ultimately necessitate compiling detailed lists oreach group o species and habitats to be explicitly protected.
The second area o protection relates to ecosystem services that are essen-
tial to human existence. Ecosystem services relevant in an agricultural context
include pollination, pest regulation, decomposition o organic matter, soil
nutrient cycling, soil structure and water regulation and purication.
5.2.2 Dinitin mnt ndpint
The second step aims at perorming an operational denition or the protec-
tion goals specied in step 1 (Table 2). Each protection goal is dened by oneor more assessment endpoints (Raybould, 2006, 2007). An assessment endpoint
is thereby dened as an “explicit expression o the environmental value that is
to be protected as set out by existing legal rameworks” (Suter, 2000). Assess-
ment endpoints are thus the valued attribute o an environmental entity
deemed worth o protection. Broad assessment endpoints tend to be less
valuable than more specic ones, but endpoints should not be too restrictive,
either. It is important to note that an assessment endpoint is not an indicator
(i.e., it is not an environmental measure generated by a monitoring program
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OPERATIONAL DEFINITION OF PROTECTION GOALS 53
that intends to be indicative o some environmental conditions), but the thingitsel to be protected. An operational denition o assessment endpoints neces-
sitates dening the ollowing criteria:
• An ecological entity being representative o the area o protection selected
(e.g., predators and parasitoids representing pest regulation)
• An attribute to be protected, or example, “abundance” or “ecological
unction”
• A unit o protection (individuals, populations, communities, guilds9)
• A quantiable spatial scale o protection10 (GM crop eld, other arable land,
nonagricultural habitats) • A quantiable temporal scale o protection (present cropping season,
ollowing cropping season, time o consent o the GM event11)
• A denition o the type o eects that are regarded to be harmul (i.e., a rele-
vant decrease in abundance or a relevant disturbance in ecological unction)
Ideally, assessment endpoints should also satisy the ollowing criteria
(adapted rom (Suter, 2007):
• As assessment endpoints are the basis or decision-making, they should
refect policy goals and societal values • Ecological entities selected should be ecologically relevant
• Ecological entities selected should be potentially highly exposed and respon-
sive to exposure
• Assessment endpoints should be operationally defnable (i.e., it should be
clearly specied what must be measured or modeled)
• Assessment endpoints should have the appropriate scale to the site or action
assessed
• Good techniques must be available to risk assessors (e.g., standard toxicity
tests, monitoring methods) to assess assessment endpoints
9 A guild denes a group o species that exploit the same class o environmental
resources in a similar way.
10 The proposed spatial scales allow a more unambiguous classication than a
classication using eld, eld borders, landscapes as the two latter terms are oten
not clearly dened. Using biodiversity conservation o plants as an example, the
proposed scales allow one to determine whether weeds are regarded a protection
goal. Weeds are only regarded to be worth o protection in case the spatial scale
o protection is extended to GM crop elds and other arable land. In case the
spatial scale or valued plants is restricted to nonagricultural habitats, weeds areexplicitly not regarded as a protection goal.
11 According to Swiss and EU legislation, the approval o a GM variety is granted
or 10 years.
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Table 2: Matrix or an operational denition o the protection goal biodiversity
or an environmental risk assessment o GM plants
54
Biodiversity
conservation
Ecosystem services /
unctions
Protected habitats
Pollination
Pest regulation
Decomposition o
organic matter
Soil nutrient
cycling (N, P)
Soil structure
Water regulation
and purication
Mammals
Birds
Amphibians
Valued insects
(e.g., butterfies)
Valued plants
Habitats listed
in legislation
Pollinating insects
Predators and
parasitoids
Soil invertebrates,
soil microorganisms
Soil microorganisms
Soil invertebrates
Fish
Aquatic invertebrates
Algae
Red List species
Species o high
conservation /
cultural value
Abundance
Ecological unction
Area o protection Ecological entity Attribute Unit o protection
Individuals
Populations
Communities
Guilds
PRoTecTIoN Goals
cRITeRIa foR THe oPeRaTIoNal DefINITIoN of THe PRoTecTIoN Goal
assessMeNT eNDPoINTs
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OPERATIONAL DEFINITION OF PROTECTION GOALS 57
be conducted as such that the dened risk hypothesis is conrmed with themaximum possible accuracy and probability. This requires that the hypoth-
esis is ocusing on detecting ecologically relevant eects. Apart rom proper
experimental design and statistical planning (Fairweather, 1991; Perry et al.,
2003; EFSA, 2009a), the rigorous testing o a hypothesis needs to answer the
question regarding under what conditions the existence o a supposed risk
is most likely revealed. For example, only i a particular stressor (e.g., the
Bt-toxin) causes a relatively strong eect under eld conditions, it will not
be blurred by a number o infuencing actors which will cause dierent,
overlapping smaller eects. Given that the infuence o the various actorsis hardly distinguishable, it could become very dicult to unambiguously
determine the causality between a particular eect and the actor causing
it. The likelihood to detect a relevant eect in an environmental multiacto-
rial setting (as typical or environmental monitoring programs) might thus be
much lower than detecting one in a more controlled setting with only a ew
actors involved. Hence, testing a risk hypothesis in a more controlled setting
such as a laboratory or greenhouse might generally be more rigorous than
testing the hypothesis under more ecological conditions (Raybould, 2007;
Romeis et al., 2008a).
5.3 appitin th mtrix r n prtin dinitin prttin g
5.3.1 apprhing n prtin dinitin th prttin g bidivrity
Operational protection goals are a prerequisite or regulatory decision-making
as they speciy what deserves protection. Assessment endpoints thereby speciy
the ecological entities and their related attributes to be specically protected
while measurement endpoints enable to select those indicators that are to be
used to determine with the maximum possible rigor the likelihood that harmmight occur (or has occurred) to the protection goals chosen. While the de-
nition o protection goals is essentially a generic process applicable to agri-
culture management at large, the more precise denition o both assessment
and measurement endpoints has to be carried out on a case-by-case basis or
each specic GM crop. A thorough problem ormulation is thereby an essential
prerequisite or the operational denition o these endpoints where the nature
o the crop introduced, the genetically modied trait and the receiving environ-
ment are considered (Romeis et al., 2008a; Wolt et al., 2010).
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Given that protection goals are set by existing legal rameworks, theinitial proposal what to protect has to be ramed by the regulatory authorities
involved in the risk analysis o GM crops. There is general consensus that biodi-
versity protection goals, as specied by existing legislation (such as Red List
species, protected habitats, etc.) (see section 4.3), are to be protected. There is,
however, controversy surrounding the necessity o the protection o “common”
species that are not explicitly listed in the legislation, but that ulll important
ecosystem services and may be reduced by common agricultural practices. The
operational denition o protection goals should thereore ideally be dened in
a transparent process involving a dialogue between all relevant stakeholders(regulators, applicants and scientists). The matrix presented herein (Table 2)
can thereby be used as a tool to structure the dialogue, especially when dening
both assessment and measurement endpoints. The process could include stake-
holder meetings where stakeholders would compile and rank dierent conser-
vation goals and ecosystem services.
Agreeing on endpoints (and thus policy targets) or biodiversity conserva-
tion and ecosystem services is likely to be a dicult task or at least two reasons.
First, the complexity o the underlying system means that endpoints are di-
cult to dene in a way that is both operational or public policy and possible tocommunicate to policy-makers and the public. Reducing these diculties by using
vague terms such as “ecological integrity” will not solve the problem. Second, the
problems are exacerbated by the act that endpoints or biodiversity conservation
and ecosystem unctioning will sometimes contradict each other. Setting ecologi-
cally-based endpoints may require balancing competing goals (e.g., the protection
o rare species vs. the preservation o common species) that are guaranteed to
be a source o controversy both or scientists and the public. The content o the
matrix will to a great extent depend on the motivations (see section 4.2.3) and
on the value systems underlying the preservation o biodiversity (see Box 2) o
the various stakeholders involved in the operational denition o protection goals.
Stakeholders will inevitably have competing motivations and values. Failures to
disclose diering motivations and value systems will have important policy impli-
cations as the operational denition o protection goal necessitates to agree on
common policy goals. The operational denition o protection goals will thereore
inevitably also include a number o challenges. Some o these challenges or a
number o ecological entities are discussed in the next section. To address these
challenges, the motivations and the values underlying the protection o biodiversity
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need to be explicitly stated and assessment and measurement endpoints need to beadapted to these motivations and values. The Ethical Reerence System presented
in section 9.2 can thereby be a tool supporting such an exercise.
Nevertheless, it is important to consider that stakeholder approaches have
limitations when it comes to decision making. Setting priorities and making
inormed decisions requires both scientic and value judgments (Failing and
Gregory, 2003). These are distinct judgments to be made by dierent individuals.
Nonscientic stakeholders should be asked to make only value judgments in
consultative processes, but not scientic judgments or which they are not quali-
ed and inormed. Evaluating the relevance o the data is a task that necessitatesexpert knowledge (see section 9.1). This is thus the task o scientists and not
o the public as the latter lacks the necessary knowledge. It is crucial to recog-
nize that decision-making requires that one considers sound science and not
democratic consideration o dierent viewpoints and interests o stakeholders.
This is because decision-making is an executive orce and not a legislative orce.
Democratic considerations have been considered during the drating o the
legislation, but once in place, the legislation has to be carried out by the regula-
tory authorities considering sound scientic principles.
Box 2: Dierent value systems underlying the preservation o biodiversity
The necessity to preserve biodiversity may, to a certain extent, be based on a scientic
rationale (Chapin et al., 2000; McCann, 2000; Tilman, 2000; Diaz et al., 2006), but the
question “why?” remains ultimately a normative one that has to be answered based on
the prevalent societal and ethical value systems. The process o nding an operational
denition o biodiversity will inevitably necessitate decision-makers to make a trade-o
as the dierent value systems oten contradict each other. These contradictions become
apparent i one compares three possible value systems that may have an infuence on
the motivation to preserve biodiversity: (1) intrinsic value, (2) demand value and (3)option value.
Intrinsic value
The idea that biodiversity is intrinsically valuable enjoys wide support as it refects that
we care or nature not as a resource, but rather as a good in itsel (Maclaurin and Sterelny,
2008). The preamble to the CBD, or example, gives an intrinsic value to biological diversity
and the ecological, genetic, social, economic, scientic, educational, cultural, recreational
and aesthetic values o biological diversity and its components (CBD, 1992).
OPERATIONAL DEFINITION OF PROTECTION GOALS 59
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Dmnd vuOne o the simplest motivations to preserve biodiversity derives rom broadly utilitarian
theories o environmental ethics (see section 9.3.1), that is, rom the idea that the moral
worth o an action is determined solely by its contribution to overall utility (e.g., to the
maximization o happiness or pleasure as summed among all persons). The value o an
ecosystem and its components thereby equates with the resources and services they provide
to humans – they have a demand value that warrants the investment required or their
conservation (Maclaurin and Sterelny, 2008). Such an approach would lead the society to
place a high value on protecting the basic ecological mechanisms on which humans depend.
A demand value approach does urthermore not tie value to diversity per se as importance is
more tied to specic uses. This may include the importance as a resource, a crucial ecolog-
ical unction or a rather obscure attribute as being loved by the general public. Following
a rather strict utilitarian theory, the demand value approach aces some challenges as the
theory can hardly aggregate individual cost benet trade-os into a collective assessment –
benets to some always impose costs on others.
optin vu
Option value, being the third utilitarian theory, links utility much more closely to diversity.
Option value is an insurance concept borrowed rom economics that is based on two basic
ideas. First, species (or ecosystems) that are not o value to us at present may becomevaluable at some point in the uture. Second, as our knowledge improves (and as circum-
stances change) we might discover new ways in which they can be valuable (Maclaurin
and Sterelny, 2008). The crucial point about option value is making diversity valuable. The
approach suggests preserving a biodiversity as rich and representative as possible as it is
not known in advance which species will prove to be important. This is probably also one o
its most obvious limitations as the approach, understood in its most broad interpretation,
would demand that everything has to be preserved just in virtue o being useul in some
conceivable uture event. This would result in the ineective goal o preserving biodiversity
in all possible respects. One solution would be to ocus not on mere possibilities, but on
probabilities that a certain eature could prove to be valuable under some circumstances
(Maclaurin and Sterelny, 2008). Species loss may not be important in terms o the role o the
species now, but rather in terms o that species being available to ulll a unctional role in
a uture environment (Thompson and Starzomski, 2007). Clearly, the option value approach
also suggests that many species do not have high enough option value to justiy major
expenditures on their conservation. The approach recognizes that many species are o great
value, but it does not imply that all species or all biological systems, are o important value
and should to be saved.
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5.3.2 exmp r m td prttin gIn the ollowing, the proposed matrix or an operational denition o biodiversity
(see section 5.2) is completed or some selected protection goals to illustrate how
such a denition could be perormed. The operational denition thereby consists
o speciying the area o protection and o dening assessment and measurement
endpoints (Table 3). Here, the protection goals are dierentiated into the two main
areas o protection, that is, biodiversity conservation and ecosystem services.
5.3.2.1 Defnition o assessment endpoints or biodiversity conservation
The rst step in the denition o assessment endpoints aims at identiying thedierent areas o protection as laid down in existing legal rameworks. For biodi-
versity conservation, the area o protection includes Red List species and species
o high conservation and cultural value. In the present example, the ecological
entities to be protected are restricted to valued plants and valued insects (in
particular, butterfies being a species group with a high conservation value where
more than 50% o the species occurring in Switzerland are Red List species).
Red List species are dened or both plants and insects (Duelli, 1994;
Gonseth, 1994; Moser et al., 2002). Similarly, species o high conservation value
and cultural value are specied in the environmental policy goals or agri-culture speciying target species12 and character species13 (Bau/BLW, 2008)
(see section 4.3.2). The unit o protection or biodiversity conservation o all o
these species is usually specied on the basis o populations or communities
and the attribute to be protected is the abundance o the respective popula-
tions and communities.
The rst diculty when dening assessment endpoint or biodiversity
conservation is the denition o the spatial scale o protection. Logically,
the spatial scale o protection or valued plants and valued insects (such as
butterfies) should be set to nonagricultural habitats as agricultural eldscannot be regarded as typical habitats or Red List species and species o
high conservation and cultural value. Typically, the primary aim o agricul-
tural elds is the production o ood and eed and not the production o
biodiversity. Yet, the promotion or conservation o biodiversity in agricul-
tural elds is a complex topic that is hotly debated in Europe. It is argued
that in many European countries, agriculture and natural habitats are inti-
mately mixed with around 70% o the land area being classied as agricul-
tural land (Hails, 2002). Consequently, the conservation o “common” species
12 Target species are locally or regionally occurring species that should be preserved
and promoted as they are threatened on a national level.
13 Character species are characteristic or a particular region and they are
representative or a specic habitat.
OPERATIONAL DEFINITION OF PROTECTION GOALS 61
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and communities within the armed landscape is seen as an emerging para-digm (Marshall et al., 2003). Hence, there is controversy about the question
whether certain common species (although not being explicitly listed in the
legislation) should be regarded as a protection goal since eects on these
species might translate to higher trophic levels. These higher trophic levels
may include Red List species or species o high conservation or cultural value.
A prominent example or the confict surrounding the protection o “common”
species are agricultural weeds that on the one hand have the potential to
reduce agricultural yield, but that do also orm an essential part o ood webs
in agricultural landscapes contributing to armland biodiversity (Watkinsonet al., 2000; Heard et al., 2005). The question is thus what characterizes a
“valued” plant species. Though there is a need to promote biodiversity not
only in nonagricultural habitats, we believe that classiying certain common
species (such as weeds) as a generic protection goal might lead to a number
o conficts. Rather, a balance between adequate weed control and the oppor-
tunity to retain some plants to support biological diversity should be searched
(see section 8.2.2).
A second diculty is linked to the denition o the temporal scale o protec-
tion. On the one hand, many legal rameworks such as the Swiss Gene Tech-nology Act require that the protection o biodiversity and its sustainable use is
permanent (GTG, SR 814.91). It is moreover known that long time periods may
be needed beore ecological eects become apparent. In the UK, it took several
decades beore marked reductions in armland biodiversity were noticed (Fuller
et al., 1995; Robinson and Sutherland, 2002). On the other hand, regulatory deci-
sions have oten to be taken within shorter timerames than decades, which
makes it necessary to nd a compromise or a measurable temporal scale. We
propose to dene the temporal scale according to the time o consent that is
granted or GM events, which is currently 10 years (European Community, 2001;GTG, SR 814.91). Ater the 10-year period, regulatory authorities can decide
whether impairment in a particular protection goal has occurred and they can
use this inormation when deciding on the renewal o consent.
5.3.2.2 Defnition o measurement endpoints or biodiversity conservation
The rst step when dening measurement endpoints or biodiversity conser-
vation consist in selecting appropriate indicator species. The term indicator is
used here according to Duelli and Obrist (2003), who dened that “an indicator
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OPERATIONAL DEFINITION OF PROTECTION GOALS 63
should be a measurable portion o an entity that correlates with this larger entity. ”On the one hand, biodiversity indicators can be dened on a more general basis
to be indicative or a larger entity such as “biodiversity in agricultural land-
scapes.” For such biodiversity assessments, several indicators such as fowering
plants, birds, and butterfies are usually combined to assure the quality o the
data obtained (Jeanneret et al., 2003; BDM, 2009). On the other hand, indicator
species can also be specically selected to test a particular risk hypothesis. I, or
example, a GM crop expresses a toxin with a specic toxicity against a particular
group o organisms (such as Cry1Ab against Lepidoptera), the risk hypothesis
should ocus on testing nontarget lepidopteran species as an eect is most prob-ably occurring in this species group (Romeis et al., 2008a).
A critical aspect when dening operational protection goals or biodiver-
sity conservation is linked to the diculty to dene measurable endpoints
or Red List species. Red List species can oten not be chosen as the primary
indicator as they can either not be tested under laboratory conditions due to
their conservation status or they occur too rarely in agricultural landscapes
to be easily monitored and to allow or proper statistical analyses (Aviron
et al., 2009). Laboratory toxicity studies and monitoring programs thereore
need to rely on surrogate species that are intended to be representative or aspecic group o Red List species. Although the utility o the concept o surro-
gate species is a constantly debated issue14 both in conservation biology (Caro
and O’Doherty, 1999) and ecotoxicological testing (Cairns, 1983), the surro-
gate approach is still the standard practice mandated or environmental risk
assessment o pesticides and GMOs in most countries. Hence, the choice o
surrogate species is most likely inevitable as it is impractical to assess biodi-
versity as a whole.
The last step in the denition o measurement endpoints or biodiversity
conservation consists o the choice o appropriate parameters or early andhigher tier studies. The term parameter is hereby used as being subsidiary
to the term indicator since eects on a given indicator are oten assessed by
the measurement o several parameters that are able to show changes in the
indicator chosen (Sanvido et al., 2005) (see section 5.2.3). “Mortality,” “devel-
opment time” or “reproduction” could, or example, be possible parameters
or early tier studies, while parameters or higher tier studies could be “abun-
dance” or “diversity.”
14 The critiques o this approach center on the question as to which species is best
suited to represent a specic group o species.
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64
Biodiversity
conservation
Ecosystem services /unctions
Pollination
Pest regulation
Decomposition o
organic matter
Valued insects
(e.g., butterfies)
Valued plants
Pollinating insects
Predators and
parasitoids
Soil invertebrates,
soil microorganisms
Red List species
Species o high
conservation /
cultural value
Abundance
Ecological unction
Area o protection Ecological entity Attribute Unit o protection
PRoTecTIoN Goals
cRITeRIa foR THe oPeRaTIoNal DefINITIoN
of THe PRoTecTIoN Goal
assessMeNT eNDPoINTs
Population
Population
Guild
Guild
Guild
Individuals
Populations
Communities
Guilds
Table 3: Examples how to use the matrix or an operational denition o protection
goals (biodiversity) or some selected protection goals
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in biological control unctions, or example, could be surveyed indirectly by recording unusual pest outbreaks (Sanvido et al., 2009). Soil invertebrates and
soil microorganisms could be surveyed by assessing decomposition o organic
matter (Knacker et al., 2003; Zurbrügg et al., 2010) or parameters such as soil
respiration and microbial biomass (Römbke, 2006; Ferreira et al., 2010).
Parameter selection or early tier studies should consider the known mode
o action o an insecticidal protein against the sensitive targets. In the case o
Cry1Ab proteins, or example, sensitive Lepidoptera larvae are killed relatively
quickly ater ingestion o the protein. Consequently, one would select “mortality”
as the appropriate parameter. In the case o an insecticidal protein that is knownto reduce the ecundity, but that is also known to have no lethal eect, the param-
eter “reproduction” would be a more appropriate endpoint than “mortality.”
OPERATIONAL DEFINITION OF PROTECTION GOALS 67
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THe Use o “THResHolDs”
To eValUaTe RIsKs aND cHaNces
CHAPTER 6
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70
6 THe Use o “THResHolDs” To eValUaTe RIsKs aND cHaNces
The idea that risks are acceptable as long as they do not exceed a certain prede-ned threshold is a concept that is oten emerging in discussions related to deci-
sion-making in risk assessments. The use o thresholds is thereby oten linked
to the issue o balancing risks and benets or more precisely risks and chances.15
When discussing the application o thresholds and the issue o balancing risks
with chances, it is important to consider that both concepts have their oundation
in specic ethical theories (i.e., either deontology or utilitarianism). Depending
on the ethical theory that is underlying the relevant legal rameworks, there
may be dierences how these concepts may be applied in a decision-making
process. The term “threshold” is urthermore oten used in dierent connota-tions in ethics and ecology. In the ollowing, the implications o these dierences
or regulatory decision-making are shortly described.
6.1 Thrhd in thi
What are the ethical criteria or acceptable risks? One option that underlies
many legal rameworks is that the risks individuals or populations are exposed
to (without their consent) are acceptable as long as they do not exceed a certain
predened threshold. Another option is that risks are acceptable (or even oblig-atory) i they are necessary or realizing the greatest expected net benet. The
rst criterion is advocated by deontological theories, the second by utilitarian
theories. It is important to note that, contrary to a widespread belie, the deon-
tological and the utilitarian criterion o risk acceptability cannot be combined
since they are mutually exclusive.
6.1.1 Dntgi pprh
According to deontological approaches (see section 9.3.2), decisions are based on
an absolute normative threshold dening a limit that no risk may exceed (Figure 1).
The main idea underlying the deontological criterion is that there is a duty o
care according to which risks should be reduced to a point where the occurrence
o harm is not to be expected. Requiring zero risk, however, cannot be justied
since this would make social lie impossible. That is why a normative threshold
is introduced. Risks exceeding this threshold are prohibited, irrespective o
the chances associated with them, while risks below the threshold are accept-
able. All options where the risk remains below the specied threshold (B & C)
15 Despite the requent use o the term “benet“ as the opposite o the term “risk,” the
term “chance“ would be the correct antonym to risk. The correct antonym to “benet“
is “damage“ as both terms describe a actual statement whereas both the terms “risk“
and “chance“ incorporate a probability component, namely, the probability that a
damage (rom a risk) or that a benet (rom a chance) might occur, respectively.
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72
or populations to certain risks, this must be done, even i these risks are very high.For each option, the total chance is compared to the total risk. There is an obligation
to choose the option with the highest expected benet (total chance minus total
risk). When ollowing a utilitarian approach, there is no normative threshold.
Utilitarianism needs a theory o intrinsic values to be able to determine risks
and chances and to weigh them up against each other. Chances reer to the prob-
ability o intrinsic value (benet) occurring, risks to the probability o intrinsic
disvalue (damage) occurring. Weighing risks and chances and summing them
up, however, presupposes a common scale, a common currency, as it were, that
allows adding and subtracting them. However, what does this currency consisto? There have been several attempts o solving this problem (or instance, by
using a monetary currency as in willingness to pay or willingness to compen-
sate), but all o them have shown to be problematic.
A urther problem aecting the determination o risks or damage is how
conficting protection goals should be weighed. O course, the law can settle this
problem by at. However, i policy makers want to preserve legal coherence,
they should try to determine the relative value o dierent protection goals by
deriving this value rom higher-order protection goals. Take, or instance, the
protection goals biodiversity and water. I there is a confict between these twoprotection goals, we need to know which o them has greater relative value with
regard to a higher-order protection goal such as the maintenance o ecosystem
stability. In many cases, the law does not suciently speciy the relation between
higher-order protection goals and subordinate protection goals. This problem
does not seem unsolvable, however. What would be needed in our example is a
determination o the instrumental, that is, unctional value o water and biodi-
versity with regard to ecosystem stability in a way that makes it clear which o
the two protection goals should be assigned priority. This determination should
be specic enough to be applicable in concrete situations where regulators mustchoose between these conficting protection goals.
6.2 Thrhd in gy
An ecological threshold can be described as a point or a zone where there is
a relatively rapid change rom one ecological condition to another (Huggett,
2005; Luck, 2005). According to this theory, at a threshold, even small changes in
environmental conditions will lead to large responses in ecosystem state variables
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THE USE OF “THRESHOLDS” TO EVALUATE RISKS AND CHANCES 73
(Groman et al., 2006; Suding and Hobbs, 2009). One idea underlying the
threshold concept is its practical use or management decisions as exceeding
specic ecological thresholds would indicate that an ecosystem is moving away
rom a desired state.16
The term threshold is closely linked to the concept o resilience, which is
oten dened as the capacity o ecological systems to recover rom disturbances(Walker, 1995). Resilience is thereby equated to the time needed or a system to
return to a global equilibrium state ollowing a perturbation. In the ecological
literature, it is thus associated with the concept o ecological stability. 17 Accord-
ingly, some authors postulate a threshold o biodiversity below which ecosystems
lose the sel-organization that enables them to provide ecological services
(Perrings and Opschoor, 1994). Ecosystems would thereby become increasingly
16 The question as to what denes a desired state includes a subjective value
judgement, a question which can not be answered rom a purely scientic and
objective perspective.
17 The term “ecological stability” is one o the most nebulous terms in ecology as up to
163 dierent denitions o the term have been counted (Grimm and Wissel 1997,
Muradian 2001).
Figure 2: Graphical scheme illustrating the utilitarian approach to balancing
risks and chances
Chance
Risk
Acceptable
Not
acceptable
Not
acceptable
a cB
Highest
expected
benet
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74
unstable as diversity decreases. As threshold patterns ollow a discontinuous,nonlinear behavior, ecosystems would not be robust enough to resist species
deletion and lose their capacity to absorb perturbations once species diversity
alls below the stability threshold. This would require that ecosystems have a
“saturation point,” that is, ecosystem services would not increase above a certain
diversity level even when biodiversity is increased. Such a pattern is quite
similar to the rivet hypothesis (Ehrlich and Ehrlich, 1981), which suggests that
ecosystems can initially aord continual removal o its component without expe-
riencing a loss o unction, while at a certain point only one additional species
extinction leads to a loss o the unction (see section 4.4).In a second denition o resilience, the existence o multiple “stable” states
in ecosystems is emphasized.18 Resilience is thereby dened as the ability o a
system to withstand changes and to maintain its structure and patterns beore
fipping to another stable state (Holling, 1973; Peterson et al., 1998; Gunderson,
2000). One key distinction between the two denitions o resilience lies in the
assumptions regarding the existence o multiple stable states. The rst deni-
tion, where resilience is essentially dened as the return time to equilibrium,
assumes that there exists only one stable state. The second one, in contrast,
presumes the existence o multiple stable states and the tolerance o the systemto perturbations that acilitate transitions among them (Gunderson, 2000).
The existence o multiple stable states and transitions between these states
have been described in a range o ecological systems, such as or example
the transition rom grassland or abandoned arable land to shrubland and
subsequently to woodland (Harmer et al., 2001; Kuiters and Slim, 2003). Both
ecological theories and empirical evidence clearly show that alternative stable
states can coexist side-by-side (Scheer and Carpenter, 2003). Landscapes
oten comprise a mosaic o patches with dierent alternative stable vegetation
types that remain unaltered or decades until an extreme event triggers a shitin the pattern
In theory, ecological thresholds must not be restricted to species extinction
leading to the collapse o ecosystem unctions, but thresholds can also be related
to habitat loss. This other theoretical pattern predicting ecological thresholds
is linked to habitat ragmentation and metapopulation models (Hanski, 1998).
Species loss may also occur due to habitat loss and ragmentation, in particular
due to the loss o habitat connectivity. Connectivity loss thereby disables the
dispersal and exchange o individuals between metapopulations occurring in
18 Ecosystems are obviously never stable in the sense that they do not change. There are
always constant fuctuations o natural populations due to seasonality and environmental
conditions (Scheer and Carpenter 2003).
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THE USE OF “THRESHOLDS” TO EVALUATE RISKS AND CHANCES 75
dierent habitat patches. As the loss o habitat connectivity is a highly nonlinearprocess, theory predicts that species loss occurs ater the degree o connectivity
has allen below a certain critical threshold. The same may be true or ecosystem
services such as biological control unctions o natural enemies where habitat
ragments support a less diverse community o natural enemies resulting in lower
predation or parasitation rates on pest populations (Kruess and Tscharntke,
1994; With et al., 2002).
6.3 Uing thrhd in rgutry diin-mking
What are the conclusions or regulatory decision-making when considering the
above mentioned ethical and ecological considerations or the use o thresholds
and in particular regarding the question under what circumstances one is
allowed to balance risks and chances? The ethical considerations are insoar
relevant as many legal rameworks such as the Swiss Gene Technology Law
are mostly based on deontological considerations. Dierent options are thereby
acceptable as long as their associated risks do not exceed a certain predened
threshold. The ethical considerations are also important when answering the
question when to balance risks and chances. Again, the deontological approachunderlying many legal rameworks determines that balancing risks and chances
between dierent options is permitted or those options where the risks o each
option remains below the given threshold. Balancing risks and chances is thus
not per se prohibited.
Using a threshold to dene damage would be an elegant approach as it
would allow more or less unambiguous decisions what represents unaccept-
able harm. In principle, every indicator value that would exceed the threshold
would be damage. Unortunately, thresholds are dicult to apply in practice as
the legal rameworks regulating the use o genetic engineering in Switzerlanddo not dene such thresholds. Without such thresholds, a coherent application
o the law is, in principle, impossible as regulatory authorities have no clearly
quantied indications that allow them to ensure the protection o human
health and the environment. Similarly, applicants (i.e., usually the companies
that intend to market a GMO) ace regulatory uncertainty as they are not able
to predict the overall costs and the time necessary or product approval. This
is in contrast to, or example, the regulation o plant protection products which
provides standard criteria or the evaluation and approval o these products
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76
in Annex 6 o the respective ordinance (PSMV, SR 916.161). I such thresh-olds are missing, it is clearly the responsibility o the regulatory authorities to
provide applicants with such thresholds as the authorities are responsible or
the execution o the law.
Based on these theoretical considerations, the dicult question to answer
rom an ecological point o view is how to dene such thresholds. We argue
that ecological thresholds or regulatory decision-making o GM crops are
dicult to apply in practice. One o the major actors inhibiting the use o
ecological thresholds in environmental management is the lack o general
principles or applying these concepts to dierent kinds o response variablesand ecosystems (Groman et al., 2006). In nature, populations usually fuctuate
around some trend or stable average and ecosystems are assumed to respond
smoothly to gradual change in external conditions. Occasionally, however, such
a scenario is interrupted by an abrupt shit to a dramatically dierent regime.
Dramatic regime shits are known or a range o ecosystems including lakes,
coral rees, oceans, orests and arid land (Scheer et al., 2001; Scheer and
Carpenter, 2003). While both theoretical hypotheses and practical examples
support the existence o discontinuities in ecological processes, it is very di-
cult to support such patterns with empirical data as most experimental studiesare not able to show a clearly discontinuous relationship between stability and
diversity (Muradian, 2001). Most studies ace the diculty to clearly dene the
characteristics o dierent alternative stable states, mainly as these are highly
dependent on the chosen temporal and spatial scales. Hence, each stressor
and ecosystem response must be evaluated independently, a process that is
usually not appropriate or regulatory decision-making as it requires years o
site-specic research. Ecological sciences are currently more able to predict
the magnitude o change (i.e., the possible alternative state) than the precise
threshold value (Muradian, 2001). With growing ecological experiences, thresh-olds or certain ecological groups may become available. Nevertheless, one has
to recognize that or most ecological indicators, ully operational thresholds
will probably rarely be available. This inevitably challenges policy-makers as
they cannot precisely rely on dened ecological thresholds that would acili-
tate decision-making processes. I thresholds are missing, damage should be
dened by using a baseline approach (see sections 7 and 8). In principle, the
baseline approach should allow one to determine when a change has to be
regarded a damage as the denition o damage is not depending on a precise
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a IRsT BaselINe aPPRoacH –
DIeReNTIaTING eecTs o DIeReNT PesT MaNaGeMeNT PRacTIces IN MaIZe
CHAPTER 7
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80
7 a IRsT BaselINe aPPRoacH – DIeReNTIaTING eecTso DIeReNT PesT MaNaGeMeNT PRacTIces IN MaIZe
7.1 Th hng ting n pprprit bin
The discussions during the rst expert workshop showed that baselines were
recognized as being a crucial point o any decision-making process as they serve
as a reerence to determine what makes a change a damage. Moreover, the base-
line approach seems to be the only practicable way o evaluating damage as the
threshold approach appears to have serious limitations that impede its practical
use in regulatory decision-making (see section 6.3).
Most people consider having an intuitive notion o the term “baseline.”However, looking at existing denitions in dierent texts, it becomes apparent
that these denitions are anything but uniorm. As a basic denition, a baseline
can be dened as “an initial set o critical observations or data used or compar-
ison or a control” (Merriam-Webster Online, 2011). The EU Directive 2004/35/EC
on environmental liability denes the term as “a reerence to assess the signif-
cance o any damage that has adverse eects on reaching or maintaining the avo-
rable conservation status o protected habitats or species. The signifcance has
to be assessed by reerence to the conservation status at the time o the damage,
the services provided by the amenities they produce and their capacity or naturalregeneration. Signifcant adverse changes to the baseline condition should be deter-
mined by means o measurable data” (European Commission, 2004). More speci-
cally, reerring to the assessment o GMOs, the European Food Saety Authority
denes the term baseline as “the current status quo, e.g., current conventional
cropping or historical agricultural or environmental data. The baseline serves as a
point o reerence against which any eects arising rom the placing on the market
o a GMO can be compared” (EFSA, 2006).
Due to the vague denitions o the term “baseline,” the use o the baseline
concept as a decision support tool remains ambiguous necessitating a moreprecise characterization. A common point pertinent to all denitions is the term
“comparison” – semantically decisions should thereore theoretically always be
taken relative to a comparator. Ultimately, the question as to what represents
environmental damage is nevertheless a legal problem. Legally, the baseline or
any evaluation o damage rom GMOs should be set by what is already regarded
representing damage today. This implies that potential damage resulting rom
GMOs should be evaluated according to the same criteria as any damage
that might occur rom other technologies, or example, chemical pesticides.19
19 Provided that there is a legal ramework regulating the technology (e.g., pesticides).
The approach is not valid or techniques that are not regulated such as the use o
mowing or tillage machinery.
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A FIRST BASELINE APPROACH 81
The implicit baseline or the evaluation o impacts o GM crops on biodiver-sity corresponds thus to current agricultural management practices where the
impact o the GM cropping system are evaluated against the impacts caused by
the cropping practices that are replaced. This leads to the question how impacts
o dierent agricultural management practice could be compared to determine
whether the impacts o the GM cropping system are lower, equal or higher than
those o current practices. A direct comparison is dicult as these impacts vary
depending on a number o dierent actors. A simple, easily applicable generic
comparison o the GM cropping practice with the most common current pest
management practice is almost impossible and beyond the scope o this report.Comparative impact assessments can thus only be perormed on a case-by-case
basis where the nature o the crop, specic aspects o the pest management prac-
tices applied and the receiving environment are considered. Dierent regulatory
rameworks are moreover used as a basis to evaluate the eects o dierent pest
management practices, which makes it almost impossible to directly compare
the eects o a GM cropping system to its conventional non-GM counterpart.
Nevertheless, an important point to consider in each comparison reers to the
act that all regulatory rameworks dierentiate between “intended” eects o
the cropping practice applied and “unintended” eects that are to be minimized.Such a dierentiation should allow outlining a generic scheme that permits to
evaluate whether the eects o dierent pest management practices are to be
regarded as intended eects (which are regarded acceptable) and unintended
eects that could represent environmental damage. This dierentiation will in
the ollowing be used to establish an approach that can help to dierentiate
between these two types o eects (see section 7.3).
7.2 c tudy 1: et Bt-miz n nntrgt rthrpd
The impacts o genetically modied Bt-maize on arthropod biodiversity in
comparison to current pest management practices used or European Corn Borer
management in maize in central and western Europe are taken as an example
to show how it is necessary to dierentiate between dierent types o eects
when evaluating environmental damage. Current crop protection practices
considered include two current (non-GM) practices (insecticides and biological
control using Trichogramma). Given that both Bt-maize and current pest control
practices display insec ticidal properties, this case study will concentrate on the
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A FIRST BASELINE APPROACH 83
which is still relatively small (approx. 4 – 5%) compared to the total area (3.3million hectares) where ECB damage is regularly above the economic injury
level in the European Union (EU-27). In addition, arming practices are used
to help manage insect pests by physically destroying pests essentially through
stalk destruction in the Fall and ploughing o maize stubbles prior to planting.
7.2.1.3 European Corn Borer control using Bt-maize
Bt-maize is genetically modied maize that carries a gene rom the soil bacte-
rium Bacillus thuringiensis (Bt). The dierent strains o B. thuringiensis contain
varying combinations o Cryproteins (so called Bt-toxins) and each o these insec-ticidal proteins is known to have a very selective toxicity against dierent groups
o arthropods (Höte and Whiteley, 1989; Schnep et al., 1998; de Maagd et al., 2001).
Bt Cry proteins are currently the only insecticidal proteins that are commercially
used in GM crops. The gene inserted into Bt-maize expresses the insecticidal
protein Cry1Ab that coners resistance to Lepidoptera (moths and butterfies).
It was initially developed to control the ECB, but has shown to be also eective
against various other lepidopteran pests, such as the Mediterranean Corn Borer
(Sesamia nonagrioides), which is restricted to the southern parts o Europe.
7.2.1.4 Environmental hazards associated with insecticides
Broad-spectrum insecticides usually have moderate to highly toxic eects on a
wide range o organisms (European Union, 2009a). Environmental impacts o
insecticides strongly vary depending on the product applied, its active substance,
the application rate, the ormulation and the application technique. For the present
case study, two active substances were selected that are used or ECB management
in maize in Europe. The rst active substance (Lambda-Cyhalothrin; a pyrethroid)
is an older broad-spectrum insecticide that is still widely used, while the second is
a more selective insecticide (Indoxacarb; an oxadioazine). Acute toxicity data or
the two active substances Lambda-Cyhalothrin and Indoxacarb are taken rom
review reports rom the EU Pesticides database (European Union, 2009a) and rom
Pesticide actsheets o the U.S. Environmental Protection Agency (EPA, 2009),
Pollinator, benecial arthropods, and butterfies: Broad-spectrum insecticides
such as Lambda-Cyhalothrin are highly toxic to a wide range o invertebrates
including honey bees. A repeatedly observed eect o many broad-spectrum
insecticides is the promotion o secondary pest outbreaks. These generally
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84
occur when insecticide applications kill natural enemies that were controllinga herbivore species that was not a pest beore. These species can then increase
to densities that cause damage. The new classes o more selective insecticides
such as Indoxacarb have several advantages over the older broad-spectrum
insecticides. Most are less likely to harm natural enemies and other nontarget
species. Indoxacarb, or example, is very eective against lepidopteran larvae,
but allows most predators and immature parasitic wasp attacking these larvae
to survive. Indoxacarb is also practically nontoxic to bees. Insecticides generally
tend to have immediate, but predominantly short-term (2–3 months) eects on
nontarget arthropods, as aected population may be able to recover due to therecruitment o new individuals rom unaected populations.
7.2.1.5 Environmental hazards associated with biological control
using Trichogramma
The egg parasitoid Trichogramma brassicae is the only invertebrate used in
augmentative biological control in maize (Bigler et al., 2010). Two ecological
concerns are discussed related to the use o this exotic species in biological
control programs in Europe. The rst concern relates to the establishment o
T. brassicae under elds conditions ollowing its dispersal into nontarget habitats.Because o their broad host range, the second concern relates to the question is
whether mass releases o T. brassicae may have ecologically signicant direct and /
or indirect eects on nontarget arthropods. Given that T. brassicae can success-
ully overwinter in diapause under Swiss climatic conditions, one can assume that
the species would establish in most regions o Europe i nontarget hosts are avail-
able. T. brassicae density increases during mass releases, but drops to prerelease
densities 2–3 weeks ater the last release, indicating that only a small raction (less
than 10%) o the released population disperses out o maize elds to nontarget
habitats. Permanent establishment occurs only in limited areas o seminatural and
natural habitats making eects on native Trichogramma populations unlikely. As
T. brassicae has a clear host plant and habitat preerence, the parasitoid does not
successully attack arthropod host eggs on other plants than maize. The eect on
lepidoptera and aphid predators under semield and eld conditions is thus very
low. Short-term mortality caused by T. brassicae in o-crop habitats is likely, but
has a negligible to low population and community eect, as the magnitude is likely
to remain below a 40% reduction in the size o nontarget lepdoptera populations.
Quantitative eects will moreover be temporary and o transient nature.
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7.2.1.6 Environmental hazards associated with Bt-maizeGiven the insecticidal properties o the Cry1Ab toxin, most concerns relate to
the question as to whether Bt-maize harms organisms other than the pest(s)
targeted by the toxin. As o May 2009, 89 original research articles have been
published addressing eects o Bt-maize (or the puried toxin) on dierent
groups o organisms both in the laboratory and in the eld (Naranjo, 2009). Most
published studies have been perormed by public research ater the approval
o the respective Bt-maize events in 1996. In addition, studies perormed by the
applicants (i.e., the company marketing the crop) have been conducted prior
to the market approval o Bt-maize (EPA, 2001; Mendelsohn et al., 2003; OECD,2007). Data or the Bt-toxin Cry1Ab are taken rom the U.S. EPA Biopesticides
registration action document on Bacillus thuringiensis plant-incorporated
protectants (EPA, 2001).
Pollinators: Honey bees are the most important pollinators o many agricultural
crops worldwide. Because o their importance to agriculture, they have been a
key test species used in environmental saety assessments o Bt-maize. These
assessments have involved comparisons o honey bee larval and adult survival
on puried Cry proteins or pollen collected rom Bt-maize versus survival onnon-Bt-maize material. A recent meta-analysis combining the results o 39
studies assessing dierent Cry proteins ound no statistically signicant eect
o Bt Cry protein treatments on survival o honey bees.
Benecial arthropods: Another important group o nontarget organisms
providing ecological and economic services within agricultural systems are
parasitoids and predators (so-called natural enemies). One hypothesis is that
Bt-maize could alter the biological control unctions o benecial arthro-
pods, which are important or controlling herbivorous insect populations inmaize. Nontarget organisms have to ingest the insecticidal protein expressed
in Bt-maize in order to be directly aected. Ingestion can occur via several
ways o exposures. Exposure can either occur by eeding on plant mate-
rial (e.g., leaves, pollen), by eeding on insects that have previously ed on
GM crops (and thereore contain the toxin) or via exposure through the envi-
ronment, e.g., when toxins rom plant residues persist in the soil. In order to be
aected by the toxin, natural enemies would moreover need to be sensitive to
Cry1Ab. Overall, several meta-analyses have shown that the majority o studies
A FIRST BASELINE APPROACH 85
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86
conducted in the laboratory and in the eld show no adverse eects on nontargetorganisms resulting rom direct toxicity o the expressed Bt-toxins (Wolenbarger
et al., 2008; Naranjo, 2009). Some laboratory studies revealed indirect prey-quality
mediated eects due to Bt-maize. Under eld conditions, these secondary trophic
eects may be caused by changes in the availability and / or the quality o target
herbivores with specialist natural enemies (oten parasitoids) depending entirely
on the target pest (i.e., the ECB). Such eects are common or any pest control
method; they are o minor concern within an environmental risk assessment
context and they should be dierentiated rom direct eects o a toxin. The weight
o considerable data available rom eld studies gives evidence that Bt-maize hasno ecologically relevant eects on a number o taxa, especially in comparison
with alternative pest control measures such as broad-spectrum insecticides. The
results conrm the high specicity o Cry1Ab having a very narrow range o
activity restricted to the target pest and closely related species. Biodiversity is
thus higher in Bt-maize elds in comparison to maize elds treated with tradi-
tional insecticides having a broader range o activity.
Butterfies: A particular ocus was laid on butterfies as Cry1Ab coners resist-
ance to Lepidoptera and as butterfies are considered to be a species group witha high aesthetic value serving as symbols or conservation awareness. Butterfy
larvae can be exposed to Cry1Ab in the vicinity o Bt-maize elds (up to approx-
imately 2 meters rom the border) when eeding on host plant leaves naturally
dusted with maize pollen during anthesis (fowering). Especially the case o the
Monarch butterfy ( Danaus plexippus) caused much public interest and led to a
debate over the risks o Bt-maize as one study had ound that when pollen rom
a commercial variety o Bt-maize (event Bt11) was spread on milkweed leaves in
the laboratory and ed to monarch butterfy larvae, ater our days almost hal o
the tested larvae died (Losey et al., 1999). Extensive ollow-up studies showedthat initial reports o toxicity o high doses o Cry1Ab toxin to butterfies in the
laboratory did not necessarily mean that there would be exposure to toxic levels
in the eld (Sears et al., 2001; Dively et al., 2004). The proportion o Monarch
butterfy population exposed to Bt-pollen in the eld was estimated to be less
than 0.8%. Although similarly detailed data is not available or Europe, the data
available provide condence that commercial cultivation o currently avail-
able Bt-maize varieties constitutes a low risk or European butterfy species.
This conclusion is based on the assumption that larval exposure to Cry1Ab is
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A FIRST BASELINE APPROACH 87
relatively low or European butterfy species considering the low expressionlevel o the toxin in pollen o the only approved Bt-maize event MON810, the
act that most pollen is deposited within a ew meters rom the eld border, and
that maize is not considered a host plant or nontarget butterfies.
7.3 apprh t dirntit t vriu pt mngmnt prti
n nntrgt rthrpd
The fow chart presented in Figure 3 proposes an approach as to how the eects
o dierent pest management practices on the arthropod auna can be dieren-tiated and compared. Eects are thereby considered within the whole system
“agricultural landscape”21 and cover both biodiversity conservation (species and
habitat diversity) and unctional biodiversity (i.e., ecosystem services) issues. The
rst part o the fow chart relates to crop protection and has to be answered based
on the spectrum o activity o the respective crop protection method applied.
Therein, the rst two questions help to dierentiate between intended eects
on target pests and other (potential) pests and unintended eects on nontarget
arthropods that may represent environmental damage. The second part o the
fow chart (Questions 3 to 11) has to be answered based on the species groupspotentially aected. Biodiversity entities potentially aected are determined
based on the Swiss environmental protection goals related to agriculture where
biodiversity is classied into three main aspects: species and habitat diversity,
genetic diversity within species and unctional biodiversity (see section 4.2.3).
Genetic diversity is thereby regarded as an important part o unctional diversity
as it is crucial to a species’ ability to adapt to its environment.
7.3.1 crp prttin
Existing regulatory rameworks acknowledge the act that agricultural manage-ment involves crop protection and that these practices inevitably comprise certain
environmental impacts. The regulation aims at ensuring that occurring impacts
are restricted to target pests, while possibly excluding unintended eects on
nontarget organisms. Three types o eects can be dierentiated when comparing
the eects o dierent crop protection practices: (1) intended eects on pests, (2)
inevitable trophic eects due to the absence o these pests and (3) unintended
eects on the arthropod auna in agricultural crops and the wider landscape.
21 Realistically, adverse eects on arthropods occur with a higher probability in crop elds
rather than outside the crop or on a landscape scale. This is basically because the exposure
o nontarget arthropods to the stressor (e.g., the insecticidal protein) is highest in crop elds.
Whether eects occurring in the crop translate to the landscape scale is depending on
a number o actors such as the magnitude o eects and the type o species aected.
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A FIRST BASELINE APPROACH 89
Potential environmentaldamage on ecosystemservice
No concern as eectcan be mitigated byrisk management
No
Possibility o mitigating eect
Resiliencepossible?
Relevant eect onecosystem service?
No
No concern as eect islikely to be temporary
No concern asecosystem service is not
signicantly aected
Considermagnitudeo eect
No
No
Yes
Key speciesgroup or ecosystemservice?
No concern asecosystem service is
likely to be stable
Yes
Yes
Yes
Intndd eect (or posi-tive side eect) o thetoxic compound applied
Trophic eect due tothe absence o pest(s)
No concern as eect isdue to the crop protec-tion method applied
No concern as eectis an invitb conse-quence o crop protection
Ecosystem services
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A FIRST BASELINE APPROACH 91
24 International Union or Conservation o Nature and Natural Resources
7.3.2 Bidivrity nrvtinQuestion 3: Does the species have a protection status?
The rst question to be answered when determining whether eects on
arthropods are aecting biodiversity conservation is whether these eects
are related to species having a particular protection status (Question 4 in
Figure 3). Three categories o species have a particular legal protection status
in Switzerland: (a) the IUCN24 Red List o threatened species being the most
comprehensive resource detailing the global conservation status o plants and
animals (Rodrigues et al., 2006), (b) species threatened on a national level and
(c) species characteristic or a specic habitat and / or region. Red Lists are a
legally binding instrument o biodiversity conservation assigning these species
an absolute protection status (NHV, SR 451.1). The two latter categories o
species are related to the overall environmental policy goal in Switzerland to
preserve and promote domestic species and their respective habitats (Duelli,
1994; Bau/BLW, 2008).
Groups o Red List species that are assigned with a specic protection
status are characterized by the availability o sucient expert knowledge to
perorm a judgment on their conservation status. For many groups o inverte-
brates, however, detailed data and expert knowledge is oten missing and theirconservation status is not known. Although being o conservation interest,
some arthropod groups are, or example, not listed in the Red Lists. Regula-
tory decision-making based on Red Lists thereore has limitations or inverte-
brates as decisions can only be made or those taxa that are listed and explicitly
protected. Ultimately, one has thus to accept that we can only evaluate what is
perceived to be important by having been listed.
Question 4: Is the species a charismatic species?
In case an eect is not related to a species having a particular protection status,the next question to be answered is whether the eect is associated with a charis-
matic species (Question 5 in Figure 3). Although not having a particular legal
protection status, a number o specie groups are regarded as being o conservation
value primarily because o their aesthetic, cultural or other relevant value. For
the arthropod auna, these include, or example, a number o butterfy and
ladybird beetle species that are not explicitly listed as either Red List species
or species threatened on a national level.
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25 Zone A – North: Denmark, Estonia, Latvia, Lithuania, Finland, and Sweden
Zone B – Center: Belgium, Czech Republic, Germany, Ireland, Luxembourg, Hungary,
Netherlands, Austria, Poland, Romania, Slovenia, Slovakia, and United Kingdom
Zone C – South: Bulgaria, Greece, Spain, France, Italy, Cyprus, Malta, and Portugal
In case a particular eect is neither related to a species with a protectionstatus nor to charismatic species, one can reasonably assume that the species
aected are judged to be o no particular value. Any eect is thus o minor
concern or biodiversity conservation and is thereore not regarded as repre-
senting environmental damage.
7.3.2.1 Consider magnitude o eect
In case a particular eect relates to either species with a protection status or to
charismatic species, one has to determine the magnitude o the environmental
impact o the specic pest management practice. The impact o a specic pestmanagement practice depends on a number o dierent infuencing actors
that vary depending on the nature o the environmental stressor (Table 4).
These actors can only be assessed on a case-by-case basis, taking into account
the conditions prevalent in a particular receiving environment. Ideally, such
an assessment would need to estimate all infuencing actors. In many cases,
however, it may not be necessary to assess all actors as the occurrence o an
eect may become highly unlikely in the absence o certain decisive actors
(e.g., because the spectrum o activity and the mode o action o the stressor
exclude a toxic eect on a particular group o valued species). Similarly, it may sometimes not be necessary to assess all actors experimentally as meaningul
estimations can be deduced rom existing data or by theoretical considera-
tions. This might be particularly relevant or those cases where it is impossible
to obtain sucient individuals or a meaningul experimental assessment, or
example, in the case o a specic Red List species. Assessments in the case
o Red List species might nevertheless also be carried out experimentally by
using appropriate surrogates.
Even or a specic crop such as maize and a pest such as the European
Corn Borer, an application-based assessment can oten only be perormed ona regional basis as pest management decisions greatly vary among regions in
Europe (Meissle et al., 2010). Dierent approaches are possible to dene what
characterizes a region. According to the new regulation on plant protection
products (European Union, 2009b), or example, the EU is divided into three
dierent geographical zones.25 Other approaches dene more detailed biogeo-
graphical regions, such as the Natura 2000 network speciying nine regions
or the SEAMzones approach proposing 12 environmental zones across the
EU (Hazeu et al., in press). Regulatory authorities demanding or regional
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A FIRST BASELINE APPROACH 93
assessments nevertheless need to consider that these need to remain practi-cable as assessments become increasingly impracticable the more regions have
to be considered.
Question 5: Is there a relevant eect on population level?
A relevant impact on biodiversity conservation is characterized by an explicit
reduction in population size o a particular species or by a clear reduction o
its area o distribution (Duelli, 1994). Such an evaluation can o course only
be perormed i the prior abundance and distribution o the species is known.
Unortunately, such data is oten not available, in particular, or most invertebrategroups that count or approximately 98% o all animal species (Duelli, 1994). The
conservation status o most species having a particular protection status is there-
ore usually deduced rom current knowledge on their specic habitat require-
ments. According to the Swiss legal rameworks, the value o a specic habitat
is judged based on the rareness o the species (potentially) being present in
this habitat (NHV, SR 451.1). In general, the rarer the species present, the more
value is given to the habitat rom a biodiversity conservation point o view. This
is based on the rationale that in case o a widespread impairment o a specic
habitat, one can reasonably assume that the species specically depending onthis habitat will be impaired too.
According to the Red List species concept, every loss is principally to be
regarded as damage as the legal rameworks assign these species a priority
status. With regard to biodiversity conservation, this would imply a zero tolerance
towards clear and widespread reductions in population size o Red List species
(i.e., a reduction o the total number o individuals o that taxon). In practice,
however, reductions in population size are most oten not abrupt, but continuous,
meaning that a particular species will not go extinct immediately. The IUCN
works with dierent Red List categories that describe the conservation statuso a particular species ranging rom extinct (EX) to least concern (LC). Species
in the categories critically endangered (CR), endangered (EN) and vulner-
able (VU) are denoted as threatened (Table 5) (Gärdenors, 2001; IUCN, 2001;
Rodrigues et al., 2006). Instead o immediate extinctions, biodiversity losses are
thereore evaluated based on transers between dierent threatened categories.
Moving a taxon rom a higher to a lower risk category is usually regarded as
being positive while transers rom categories o lower risk to higher risk indi-
cate biodiversity losses.
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Bt-miz
sTRessoR-RelaTeD
Spectrum o activity and mode o action o the stressor
produced by the transgenic trait
Susceptibility o organism to the insecticidal protein
Amount o stressor present in the environment based on
the ollowing actors a–d
Spatial distribution o Bt-maize in the landscape
(depending on the percentage o maize cultivation in
a given region and the adoption rate o Bt-maize)
Amount o insecticidal protein expressed in a specic
plant tissue based on temporal expression levels and
patterns
Dispersal o the stressor in the environment based on
pollen distribution patterns, root exudates, crop residues
(i stressor is expressed in these tissues)
Degradation o the stressor in the environment based on
environmental ate
Temporal duration o exposure based on timing, dura-
tion and intensity o the stressor being present in the
environment
PRoTecTIoN Goal-RelaTeD
Number o individuals / proportion o the populationexposed to the stressor based on the ollowing actors a–c
Occurrence and spatial distribution (regional,
landscape, habitat) o a valued species or its sensitive
lie stages
Occurrence and spatial distribution o the species’ host
plants (i applicable)
Amount o plant tissue consumed by organisms in the
sensitive lie stage
Table 4: Factors infuencing the
magnitude o environmental impacts
o Bt-maize, insecticide applications
and biological control organisms
that have to be considered when
determining whether ecologically
relevant eects on population level
o valued species occur (ecological
relevance is determined based
on questions 5 – 7 and 9 – 11 in
Figure 3, respectively) (adapted
and expanded based on Sears
et al., 2001).
8
1
2
3
a
b
c
d
4
5
a
b
c
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A FIRST BASELINE APPROACH 95
Intiid
Spectrum o activity and mode o action o active ingre-
dient o the insecticide
Susceptibility o organism to the active ingredient
Amount o stressor present in the environment based on
Percentage and spatial distribution o maize elds in
the landscape where the insecticide is applied
Amount o insecticide active ingredient present on crops
and / or host plants (depending on deposition rate)
Dispersal o the insecticide in the environment based
on ormulation, application technique, drit actor and
vegetation distribution actor
Degradation o the active ingredient in the environment
based on environmental ate o the active substance
and ormulation
Temporal duration o exposure based on timing,
duration and application rate o the insecticide
Number o individuals / percentage o the populationexposed to the stressor based on
Occurrence and spatial distribution (regional,
landscape, habitat) o a valued species or its
sensitive lie stages
Occurrence and spatial distribution o the species’
host plants (i applicable)
Amount o stressor ingested or contacted by organisms
in the sensitive lie stages
Bigi ntr gnt (Trichogramma)
Host range o T. brassicae
Parasitation rate o T. brassicae
Number o adult parasitoids present in the
environment based on
Percentage and spatial distribution o maize elds
in the landscape where T. brassicae is released
Amount o emales o T. brassicae deployed
in maize elds
Dispersal rate o parasitoids outside o maize elds
Survival o adult parasitoids in the environment
Temporal duration o exposure based on timing,
duration and number o applications o T. brassicae
Number o individuals / percentage o the populationexposed to the stressor based on
Occurrence and spatial distribution (regional,
landscape, habitat) o a valued species or its
sensitive lie stages
Occurrence and spatial distribution o the species’
host plants (i applicable)
Number o hosts encountered by adult parasitoids
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96
10
PoPUlaTIoN ReDUcTIoN
(past, present and / or projected)
Observed reduction that is clearly reversible AND
understood AND ceased
Observed reduction that may not have ceased OR may not
be clearly understood OR may not be clearly reversible
Projected or suspected population reduction
up to a maximum o 100 years
Observed reduction where the time period includes both
the past and the uture
GeoGRaPHIc RaNGe (either B1 or B2)
Extent o Occurrence (EOO) (see ootnote 23)
Area o Occupancy (AOO) (see ootnote 24)
and 2 o the ollowing 3
Severely ragmented locations
Continuing decline
Extreme fuctuationssMall PoPUlaTIoN sIZe aND DeclINe
Number o mature individuals (and either C1 or C2)
Estimated continuing decline up to a maximum o
100 years
Continuing decline
(a i) o mature individuals in largest subpopulation
(a ii) or % mature individuals
(b) extreme fuctuations in the number o mature
individuals
VeRY sMall oR ResTRIcTeD PoPUlaTIoNs
Either Number o individuals
or Restricted AOO
QUaNTITaTIVe aNalYsIs
Probability o extinction in the wild is at least
Table 5: Summary o the ve criteria
(A – E) used to evaluate i a taxon
belongs to a threatened Red List
species category (modied based
on IUCN, 2008).
9
A
A1
A2
A3
A4
B
B1
B2
C
C1
C2
D
E
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A FIRST BASELINE APPROACH 97
critiy ndngrd
> 90%
> 80%
> 80%
> 80%
< 100 km2
< 10 km2
= 1
n.a.
n.a.
< 250
25% in 3 years or 1 generation
< 50
90–100%
n.a.
< 50
n.a.
50% in 10 years or 3 generations
(max. 100 years)
endngrd
> 70%
> 50%
> 50%
> 50%
< 5000 km2
< 500 km2
≤ 5
n.a.
n.a.
< 2500
20% in 5 years or 2 generations
< 250
95–100%
n.a.
< 250
n.a.
20% in 20 years or 5 generations
(max. 100 years)
Vunrb
> 50%
> 30%
> 30%
> 30%
< 20,000 km2
< 2000 km2
≤ 10
n.a.
n.a.
< 10,000
10% in 10 years or 3 generations
< 1000
100%
n.a.
< 1’000
AOO > 20 km2 or # locations ≤ 5
10% in 100 years
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A FIRST BASELINE APPROACH 99
Question 6: Is it possible to tolerate biodiversity losses o species witha protection status or o charismatic species?
Rare species in agricultural landscapes are oten remains o ancient agricul-
tural practices. Historically, low intensity land management has resulted in a
rich assemblage o species in agricultural landscapes (Stoate et al., 2009). Over
centuries, anthropogenic infuences shaped the initial woodland prevalent in
Central and Western Europe into a cultural landscape dominated by rural activi-
ties. Dierent agricultural management practices divided the landscape into a
multitude o diverse habitats that allowed a wide variety o species to colonize
the newly created habitats. This resulted in an increase o biodiversity prior tothe industrialization o agriculture in the middle o the last century. It has been
estimated that 50% o all species in Europe depend on agricultural habitats,
including a number o threatened and endemic species (Stoate et al., 2009). Yet,
agricultural intensication over the past 60 years has led to signicant impacts
on the environment. The mechanization o agriculture has acilitated degrada-
tion in habitat quality and increasing habitat homogeneity. This led to the elimi-
nation o many landscape elements and habitats that were typical or a number
o specialized taxa. The species richness and habitat diversity o nearly all arm-
land has urthermore declined due to more intensive eld management, that is,among others higher pesticide and ertilizer use and the simplication o crop
rotations (Stoate et al., 2001; Robinson and Sutherland, 2002; Tilman et al., 2002).
Species present in agricultural landscapes today tend to be habitat generalists.
One may thus argue that the ew rare species occurring in agricultural land-
scapes are particularly valuable as their habitats are predominantly threatened
rom disturbances and habitat loss.
When evaluating widespread biodiversity losses in agricultural landscapes,
one may ask whether certain reductions in the population size o protected or o
charismatic species are tolerable. In the ollowing, we will argue that local biodi- versity losses o protected species may, to a certain extent, be tolerable i popula-
tions o that taxon still occur or may develop in other, undisturbed habitats. The
argument is related to the dilemma that Red Lists are oten used (or even laid
down in existing legal rameworks) on a national or on a regional level, but were
initially developed to assess extinction risk o entire populations o species at
the global level. The use o Red Lists at the national level may thus be misleading
as a population can be distributed over more than one country, which makes it
dicult to estimate the extinction risk o the part o the population resident
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A FIRST BASELINE APPROACH 101
In conclusion, eects on arthropod biodiversity are only to be regardedas potential ecological damage in case biodiversity losses are related to either
species with a protection status or to charismatic species. It is moreover impor-
tant to determine whether the population losses are widespread and o a high
magnitude and whether certain actors apply that might allow tolerating the risk
or biodiversity losses (e.g., in case they do not relate to endemic species that are
particularly characteristic or Switzerland). Finally, damage only occurs i it is
impossible to mitigate the biodiversity losses.
7.3.3 eytm rviI an eect on arthropod biodiversity is not related to a biodiversity conser-
vation issue, it may be related to an ecosystem service. Ecosystem services
are those properties o ecosystems (e.g., climate regulation, nutrient cycling,
pollination, and provision o ood and ber) that either directly or indirectly
benet human activities (Hooper et al., 2005; EASAC, 2009). Rationales or the
protection o biodiversity are oten based on the argument that species provide
these ecological goods and services that are essential or human welare (see
section 4.2.3).
Question 8: May certain species be lost without impairing
the ecosystem function?
In contrast to biodiversity conservation issues, where the ocus o conserva-
tion is clearly laid on specic species to be protected, it is less clearly dened
how many and which species provide a specic ecosystem service (see section
4.4.2). One o the most important ecosystem services provided by arthropods in
agricultural landscapes is the biological control o arthropod pests within crops
elds (Kruess and Tscharntke, 1994; Wilby and Thomas, 2002; Kremen, 2005;
Tscharntke et al., 2005). A crucial question when determining what representsenvironmental damage in this context is thus whether certain species may be lost
without impairing the ecosystem unction as the species are redundant (Ques-
tion 9 in Figure 3). This leads to the question as to whether there is a unctional
relationship between species diversity and ecosystem unction, that is, whether
more species generally lead to more stable ecosystem services. Available data
show that species richness oten seems to be not so important or agroecosystem
unction, as even only one or a ew species might ensure a particular unction
(Hooper et al., 2005; Moonen and Barberi, 2008; Shennan, 2008)(see section 4.4).
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102
There is nevertheless convincing evidence that species-rich systems deliverecosystem services more reliably than species-poor ones. This is because in
diverse communities, redundancy among species can buer processes in response
to changing environmental conditions and species losses. Ecosystem services
typically do, however, oten not depend on the presence o specic species, espe-
cially not rare, narrowly distributed species. They more likely depend on common
and widespread species than on rare species (Diaz et al., 2006; Maclaurin and
Sterelny, 2008). From a unctional point o view, reductions in population size o
a redundant species may thus be tolerable and be o no concern i the unction
is ullled by other species. In case a species is not redundant, one has to deter-mine the magnitude and the spatial extent o the impact to evaluate whether its
loss constitutes environmental damage (Question 10 in Figure 3).
7.3.3.1 Consider magnitude o eects
The actors to be considered when taking into account the magnitude o eects
on ecosystem services are principally comparable to those relevant or biodiver-
sity conservation issues (see Table 4) as unctions are ultimately also carried our
by specic species groups.
Question 9: Is there a relevant eect on an ecosystem service?
Potential ecological damage on ecosystem unctions occurs i there is a relevant
impact on population level o a nonredundant species responsible or a particular
ecosystem service. This is essentially the case i local reductions in population
size are not buered in due time by migration rom other populations occurring
in nearby habitat patches. Changes in ecosystem unctions are usually dicult
to assess as the precise nature o a particular unction is oten unknown. It is, or
example, oten not known how much a particular species contributes to a speci-
ic unction such as biological control o pest species. In contrast to biodiversity conservation issues, where population reductions o valued species can normally
be assessed directly, ecosystem unctions usually have to be assessed indirectly.
By analyzing the general state o ecosystem unctions, one obtains a more accu-
rate indication whether unctional biodiversity is aected. An indirect survey
can be perormed by recording an indicator able to demonstrate a ailure in the
unction. Failures in biological control unctions, or example, can be assessed
more accurately by observing unusual pest outbreaks rather than by monitoring
specic groups o natural enemies (Sanvido et al., 2009).
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104
regulatory rameworks. This leads to the somehow irrational situation that thesame impacts may be judged dierently depending on what pest management
practice caused them. This contradicts the initial assumption that the baseline
or any evaluation o damage rom GM crops is legally set by what is already
regarded representing damage today. In our opinion, this dilemma is one o the
most important open question that has to be resolved when discussing what
baseline has to be considered when evaluating environmental impacts o GM
crops. As long as pest management practices having similar impacts on the
environment are regulated dierently, it will not be possible to nd a reason-
able solution to determine a baseline suitable or regulatory decision-makingo GM crops. This dilemma is particularly incoherent when considering that the
use o broad-spectrum insecticides is generally known to have wider environ-
mental impacts than the use o Bt-maize (Romeis et al., 2008b; Wolenbarger
et al., 2008; Naranjo, 2009).
The rst question that arises rom the present case study is whether the
risks o the dierent pest management practices or biodiversity should be
evaluated based on their specic impacts on single groups o species or based
on an overall sum o impacts. A comparison based on the overall sum o impacts
on biodiversity might actually be useul in practice to allow decision-makerscomparing the ecological ootprint o dierent agricultural management prac-
tices, but current legislation does oten not allow decisions based on averaged
risk. Regulatory decisions are usually based on absolute risks, meaning that i
a technology is harmul it will not get approval because another technology is
more harmul. Similarly, risks are not averaged – a technology does not obtain
approval just because there is no risk or certain groups o organism i there is
a high risk or other groups o organisms. The case study is thus probably more
relevant or a comparison o the ecological impacts o dierent crop protec-
tion methods on a particular group o organisms than or a comparison o theoverall risks.
Second, the question arises as to what agricultural management practice
is to be considered as a comparator when perorming such an evaluation or
Bt-maize. One could argue that a “no treatment” scenario would be an appro-
priate baseline considering that only a small percentage (approx. 5 – 20%) o
the maize area in Europe is sprayed with insecticides against the ECB and 5%
is treated with Trichogramma (see section 7.2.1). However, this argument is in
our opinion not a logical rationale supporting a “no treatment” scenario as a
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A FIRST BASELINE APPROACH 105
realistic baseline since the act that approximately 75% o the maize area is nottreated against the ECB is primarily an economic decision taken by armers.
This decision is oten due to ECB damage remaining below the economic injury
level and technical diculties to apply insecticides in tall maize. This results
in a lack o protability o the control methods available. Since armers would
have the option to use approved insecticides or Trichogramma, these should
also be used as a comparator or a current management practice.
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a secoND BaselINe aPPRoacH –
DIeReNTIaTING eecTs o DIeReNT WeeD MaNaGeMeNT PRacTIces IN MaIZe
CHAPTER 8
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A SECOND BASELINE APPROACH 109
economically acceptable threshold level. Weed control in maize is alwaysnecessary in temperate climates during the critical growth stage. Since maize
develops slowly ater seeding in comparison to native weeds, the crop has
to be protected rom weed competition between the 2- and 8-lea stages to
prevent yield losses (Ammon, 1993; Häni et al., 2006; Dewar, 2009). Weeds may
be controlled by mechanical weeding and / or by the use o synthetic herbicides.
Weed control in conventional maize cultivation typically includes tillage prior
to sowing and usually up to two pre- and post-emergence herbicide treatments.
In Switzerland, or example, approximately 85% o the conventional maize area
is ploughed prior to sowing, while only 15% are cultivated using conservationtillage practices (Häni et al., 2006).
8.2.1.2 Hazards o current weed management practices in maize
Conventional weed management practices in maize are usually based on using
an herbicide mix containing a combination o three to our active ingredients
(Devos et al., 2008; Dewar, 2009). This allows armers to establish locally adapted
herbicide regimes that consider the weed species present, as well as soil type
and conditions.
Direct toxic eects o herbicides
Although there have been herbicides that were toxic to humans and dangerous
to handle or armers, most o these products are no longer used in Euro-
pean agriculture and they have been replaced by newer products. Many newer
herbicides used in conventional maize possess little or no direct toxicity to
mammals, birds, earthworms, bees and benecial arthropods as herbicides
target highly specic biological or biochemical processes within plants. Some
o the herbicides used in conventional cropping systems may show direct toxic
eects on aquatic organism.
Indirect eects o herbicides
The intensive use o herbicides may promote a number o indirect environmental
eects such as the development o resistances in weeds, the enhancement o soil
erosion and the contamination o surace water. These concerns are however
independent rom the use o either conventionally bred or GMHT varieties, but
a result o the herbicide regime applied.
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110
Impacts o tillage on soilMost armers use tillage (ploughing) to prepare the soil or planting. Excessive
tillage, however, is known to cause soil structure changes, increase the suscep-
tibility to soil erosion and reduce soil moisture. Loss o top soil due to tillage
may cause environmental degradation that can last or centuries. Ploughing is
also known to be the most destructive cultivation method aecting invertebrate
populations through physical destruction, desiccation, depletion o ood and
increased exposure to predators (Stoate et al., 2001).
8.2.1.3 Weed management using GM herbicide-tolerant maizeGenetically modied herbicide-tolerant (GMHT) crops permit the use o broad
spectrum herbicides such as glyphosate (Roundup Ready®) or gluosinate-
ammonium (Liberty®) at the postemergence phase. Growing GMHT crops
allows growers to use one broad-spectrum herbicide controlling a wide range
o both broadlea and grass weeds instead o several herbicides. GMHT maize
is presently primarily cultivated in the United States. Up to a ew years ago,
GMHT maize varieties only accounted or about 10 – 20% o the U.S. maize
acreage mainly because GMHT varieties were not available in many o the
most popular hybrid varieties and as these varieties were not approved orimport into Europe (Gianessi, 2005). Slower adoption o GMHT maize may also
have been due to the act that many armers are able to control weeds in maize
by conventional weed management at moderate costs. Farmers using GMHT
maize varieties generally have dicult-to-control weed problems that require
more costly programs, especially as conventional herbicide regimes may not
always provide consistent season-long control. With the increasing adoption
o stacked GM maize varieties in the U.S., the use o GMHT in combination
with insect-resistance is growing. In the European Union, GMHT maize is
currently not approved or commercial cultivation, but several applicationsare pending. Several GMHT maize events are approved or importation into
the EU as ood and eed.
A similar herbicide regime as with GMHT maize can be applied when using
Cleareld® maize varieties that are tolerant to the broad-spectrum herbicide
imidazolinone. Given that these varieties have been developed by traditional
breeding, the use o these varieties is however not specically regulated as or
GM crops.
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8.2.1.5 Uncertainties related to the environmental impacts o GMHT maizeAs no GMHT maize has been approved or commercial cultivation in the EU,
there are currently theoretical experiences on how weed management in
Europe would change under real agricultural conditions (Devos et al., 2008;
Dewar, 2009). Environmental impacts due to crop management changes are
usually dicult to assess because they are oten caused by many interacting
actors and do only show up ater an extended period o time. Considering
the widespread eects modern agricultural systems had in the last decades,
changes in management practices are probably among the most infuential
actors that could lead to biodiversity changes. It is, however, crucial to bearin mind that management changes are not limited to the adoption o GMHT
crops. They do occur in any (non-GM) crop management strategy, and could
also be caused by the adoption o new pesticides, cultivation techniques or
crop varieties.
8.2.1.6 Potential environmental chances o growing herbicide-tolerant crops
Mitigation o negative environmental impacts o soil tillage
The negative environmental impacts caused by tillage operations can be miti-
gated by the application o conservation tillage. GMHT varieties acilitatearmers to adopt conservation tillage practices (Dewar, 2009; NRC, 2010). Since
weed control can be done during the postemergence phase, there is no need
or pre-seeding tillage and direct-seeding techniques can be applied. These
conservation tillage practices leave a layer o plant residues on the soil sur-
ace, preventing soil erosion, reducing evaporation and increasing the ability
o the soil to absorb moisture. A richer soil biota develops that can improve
nutrient recycling. Earthworm populations are generally higher in no-till elds
than in ploughed elds. There is also evidence that conservation tillage can
provide a wide range o chances to armland biodiversity by improving agri-cultural land as habitat or wildlie (Holland, 2004). The greater availability o
crop residues and weed seeds can improve ood supplies or insects, birds, and
small mammals. In addition to a reduction in soil erosion and degradation, less
requent soil cultivation also results in a decrease in the emission o green-
house gases, partly arising rom a reduction in uel use (Brookes and Baroot,
2005; Burney and Lobell, 2010).
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Lower toxicity o the herbicides used with herbicide-tolerant cropsAlthough new herbicides show a relatively low toxicity, glyphosate and gluosi-
nate ammonium are less toxic to human health and the environment compared
to the replaced herbicides. In addition, they do not move readily to ground water,
resulting in ewer losses o chemicals by leaching and run-o rom the eld (Duke,
2005; Fernandez-Cornejo and Caswell, 2006; Devos et al., 2008; Dewar, 2009).
8.2.2 a rik mnt pprh r GMHT miz
Discussions among participants o the second expert workshop showed
consensus that there were no undamental dierences in how to approach a riskassessment or GMHT maize and Bt-maize apart rom the problem ormulation
that has to consider indirect eects or GMHT maize as well. An environmental
risk assessment o GMHT crops thus raises two major concerns: (1) direct toxic
eects and (2) indirect ood web eects.
8.2.2.1 Direct toxic eects o GMHT maize
Two types o direct toxicity have to be considered related to GMHT crops: (a)
eects resulting rom the genetic modication due to the expression o a novel
protein enabling the herbicide tolerance and (b) toxic eects caused by theherbicide applied.
Effects caused by the novel protein: Tolerance to glyphosate is enabled by the
introduction o a gene coding or 5-enolpyruvylshikimate-3-phosphate synthase
(EPSPS) rom Agrobacterium sp. As EPSPS enzymes occur in a wide range o
plants and ungi, and in some microorganisms, humans and the environment
have a long history o dietary exposure to these proteins. No adverse eects
have been reported with their intake (EFSA, 2009b). The same applies or the
gene coding or PPT-acetyltranserase (PAT) that is responsible or toleranceto gluosinate-ammonium. The PAT gene was originally isolated rom Strep-
tomyces viridochromogenes, an aerobic soil actinomycete. The PAT enzyme is
thereore naturally occurring in the soil and there are extensive studies showing
the saety and specicity o this enzyme.
Toxic eects caused by the herbicide applied: There is currently a debate among
dierent regulatory bodies in the EU under what regulation direct eects o
the herbicides used with GMHT crops have to be assessed. In principle, both
A SECOND BASELINE APPROACH 113
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in environmental chances compared with the conventional practice.Depending on the herbicide management chosen, it can either enhance
weed seed banks and Autumn bird ood availability, or provide early
season chances to invertebrates and nesting birds (Ammon, 1993;
Dewar et al., 2003; May et al., 2005).
c. A technical approach o leaving a proportion o rows o arable elds
unsprayed to promote the growth o fowering and seedling arable
weeds (Pidgeon et al., 2007). Model calculations or GMHT sugar beets,
or example, have shown that leaving one row in every 50 unsprayed
would achieve a weed seed production equivalent to current conven-tional practice.
2. A more specic option aiming at managing low populations o “benecial
weeds” in the eld. Benecial weed species are characterized by a low level
o competition with the crop and by having a potential value as a resource or
higher trophic groups (Storkey and Westbury, 2007). Under standard weed
management practices, such less competitive annual broadlea plants tend
to have a selective disadvantage compared to competitive perennial species
including many grass weed species.31 Grass weed species tend to be relatively
poor resources or higher trophic groups. Lists o benecial weed speciesshowing a positive number o associated insect species, being part o the
diets o armland birds and showing a low to moderate competitive ability
with crops have been published (Marshall et al., 2003). Weed management
practices can be adapted to promote benecial weeds by relying on selective
herbicides that control grass weed inestations while leaving most broadlea
species (Storkey and Westbury, 2007).
8.2.3 appitin th prpd pprh
The above mentioned considerations show that one o the main challenges oran ERA o GMHT crops is developing a meaningul problem ormulation. In
contrast to an ERA or an insecticidal crop such as Bt-maize, where the risk
consists in more or less probable adverse eects on other organism than the
target pest, the range o indirect impacts on armland biodiversity that could
occur due to the adoption o GMHT crops is very large. This makes it di-
cult to ormulate clear risk hypotheses that could be tested, especially as the
conceivable impacts are oten more or less vague concerns than risks in the
pure sense o the term. At least rom an ecological point o view, perorming a
A SECOND BASELINE APPROACH 117
31 The shit rom broad-lea weed species to grass weeds has urthermore been avored
by the shit rom Spring to Autumn sowing dates due to the planting o Winter cereals
(Storkey and Westbury 2007).
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ETHICAL REFERENCE SYSTEM TO ASSESS BIODIVERSITY 125
35 One could raise the objection that ethical considerations taking place within the law, as
it were, must take into account the “act o pluralism,” that is, the need to recognise a
multiplicity o perspectives in the ethical debate, in the sense that none o the pertinent
theories can simply be dismissed as irrational. This objection could be justied by
arguing that a modern constitutional state cannot be guided by the undamental
ethical principles o one specic ethical theory. Instead it is required to listen to the
dierent standpoints in order to base its own activity on a minimum ethical consensus.
This is the only way that the state can avoid being in thrall to particular groups andpreserve its ideological neutrality. This argument, however, is not plausible. I ethical
refections are a part o the executive process, there is no point in demanding that the
regulatory authorities should strive or a minimal consensus. Rather, the aim should
be to ensure that the best possible arguments prevail. For this reason, the authorities
involved should base their decisions on expert opinion, that is, on the expertise o
proessional ethicists.
decision-making such as the EM. As ar as risk assessment is concerned,ethics could either clariy on which ethical theory or theories the legal criteria
or acceptable risks are based or it could contribute to developing clearer and
more concrete criteria or acceptable risks. The ormer would help regulators
to better understand the normative basis o their decisions. The latter would
help them to better justiy and improve the quality o their decisions.
This critique o the EM, based on a scientic – and thereore allibilistic –
conception o ethics, was the starting-point or preparing the second workshop.
The conclusions to be drawn rom the ailure o the EM to deliver what wasoriginally hoped or are clear. In order to develop ethical criteria or regulatory
decision-making regarding the question o acceptable risks o GM crops or
biodiversity, one must proceed as ollows:
• Systematically develop possible ethical criteria or assessing changes in
biodiversity and evaluating the risks o biodiversity loss in agriculture.
• As these criteria are theory-based, the next step is to choose the most plau-
sible systematic normative ethical theory and spell out what this entails or
the acceptability o risks o biodiversity changes in agriculture.
• Apply these criteria to the issue o evaluating environmental impacts o GMcrops on biodiversity (in the context o a comparative risk assessment).
The time-consuming rst step was taken beore and during the second work-
shop. Special care was taken to ormulate all systematically relevant ethical options
o assessing changes in biodiversity and the risks associated with it. The result
is a new “ethical matrix” which, as the discussions during the second workshop
clearly showed, does not only have the advantage o systematic completeness. It
also allows regulators to nd out or themselves which normative ethical theory
they avor. Moreover, it helps them understand which ethical theory or ethical
considerations underlie the legal regulations on which they base their decisions.
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130
Direct
Indirect
Direct
Indirect
Deontological
Utilitarian
Deontological
Utilitarian
Bintri
entri
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ETHICAL REFERENCE SYSTEM TO ASSESS BIODIVERSITY 133
such as octopuses and squids). Whether invertebrates and plants are sentient iscontentious. In the ollowing, we will assume that invertebrates and plants are
not sentient, that is, they are not able to eel pleasure and pain. From a patho-
centric perspective, the value o biodiversity is purely instrumental deriving
rom its unction or the survival or well-being o sentient beings.
3. Biocentrism: All and only living beings count morally or their own sake.
According to biocentrism, it ought to be respected that living beings have a
“good o their own.” This kind o good is dened as the one being essential or
the fourishing o living beings. It is usually based on the telos (purpose) o arespective species (that can only realize itsel in individual beings). It is what
constitutes their inherent worth (Eigenwert). That is, or example, why we do
not respect an indoor plant i we let it wither.
Harm is thus not bound to pain and suering as in pathocentrism, but
to fourishing. A living being is harmed to the extent that it is hindered rom
leading a species-appropriate lie – a lie that is typical or ideal o beings o its
kind – or rom unolding its individual capacities and talents. From a biocen-
tric viewpoint, biodiversity does not have a value o its own. It is valuable only
insoar as it is indispensable or useul or the survival or well-being o indi- vidual living beings o any kind.
4. Ecocentrism: Not only individual living beings, but also nonliving individual
entities such as stones and collective entities such as populations, habitats,
ecosystems, rivers or species count morally or their own sake, irrespective o
their importance or individual living beings.
Ecocentrism implies that not only individual living beings, but also entities
such as ecosystems or populations or nature as a whole can be in a good or a
bad condition or state, and that they can be harmed as such. This is becausethey also have a good o their own and can thereore fourish or be prevented
rom fourishing. In ecocentrism, biodiversity is regarded as a real – as opposed
to a nominal – entity.39 This entity ought to be protected as such because o its
inherent worth. This protection may be morally required even i it is against the
interests o living beings, human beings included.
39 Real means that the concept “biodiversity” is equivalent to an actual entity “out there”
in the world. “Nominal” means that the concept “biodiversity” is just an abstract
concept o classication (i.e., certain eatures or groups o eatures in the world are
subsumed under one term without claiming that there is something out there that is
common to all o these eatures thereby constituting biodiversity).
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9.3.2 Dntgy Deontological theories claim that the ethical assessment o actions must not be
based on their consequences alone. From a deontological point o view, certain
acts are morally wrong in themselves, that is, irrespective o their consequences
(such as the intentional killing o an innocent person). Such acts are prohibited
even i they would increase or maximize net benet. Moral prohibitions o this
deontological kind serve as constraints with regard to utilitarian considerations
o total utility.
One way to conceptualize this idea o constraints is to reer to moral rights.
To say, or example, that an individual being has a moral right to lie means thatthis right must be respected even i disrespecting it would lead to an increase o
the total amount o value. In other words, this being should not to be killed even
i killing it would increase or maximize total utility.
Concerning the ethical assessment o risks, deontological theories imply
dening threshold values. Risks that are above a threshold value are morally
prohibited, whereas risks below such a value are permissible or acceptable.
The general risk ethical criterion is the criterion o due diligence or duty o
care. According to this criterion, other beings may only be exposed to a risk i
the risk-exposing person (or institution) has taken all necessary precautionary measures to avoid – with the highest probability easible – the occurrence o a
potential harm.
The general idea underlying the criterion o duty o care is as ollows: the
concept o harm is dened by reerence to moral rights – inringing on these
rights means causing harm to the right-holder. Such harm is morally unjustied
even i by inficting it, one increases total utility.41 Which rights exist depends on
the normative background theory. Most theories would agree on moral rights,
such as, among others, the right to dispose o one’s own body and one’s own lie,
a right to bodily integrity, a right to reely choose one’s own way o lie, a right toproperty and a right to lie.
To extend the harm principle – the prohibition to inringe on other being’s
rights without their consent – to all situations where others are exposed to a
risk, that is, to demand zero risk and thus to require that others ought not to be
exposed to any risk, cannot work in real lie or a undamental reason: it would
ETHICAL REFERENCE SYSTEM TO ASSESS BIODIVERSITY 135
41 This is a provisional conception. It may be more plausible to decouple the concept o
harm completely rom the concept o the inringement or violation o moral rights.Consequently, there would be no moral harm. Harm would always be prudential
harm. As ar as moral rights are concerned, their violation would, o course, remain
morally wrong, but it would not be a harm inficted on the being(s) whose right(s)
is (are) violated. This conception, however, would not change the risk criterion as
sketched above. The core idea would still be using threshold values regarding the
violation o moral rights in order to separate acceptable rom inacceptable risks.
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The risk o a reduction in biodiversity outside agricultural land due to cultiva-tion practices is irrelevant in this context, insoar as no individual property right
is aected. There is no probability that this right may be violated. From an anthro-
pocentric-deontological perspective, there is no other moral right that could play
a role in this context as there is no individual moral right to biodiversity.
With regard to the indirect assessment, the question is whether the armer
exposes other human beings on his land or on other armer’s land or outside
arable land to a risk. In order to be a risk, there must be a probability that biodi-
versity losses would violate certain moral rights o these humans. O the rights
mentioned above, the only relevant right is the right to lie and limb (bodily integrity). It is questionable, however, whether there is any probability (higher
than zero) that this right could be negatively aected by a reduction in biodiver-
sity. In the case that this would be possible, the deontological approach would
again determine a threshold value. Again, the decisive point would be that the
probability o a harm occurring must be very low.
Utilitarian anthropocentrism
According to utilitarianism, one ought to choose the action that maximizes the
expectation value or all those being aected – in this case, or all human beings who are aected.43 As ar as the armer’s own land is concerned, there are two
scenarios. In the rst scenario, he is the only human being aected by a loss o
biodiversity. Supposing that utilitarianism advocates duties to onesel, that is,
a moral duty to maximize one’s own happiness, one could argue that he must
calculate the possible (economic) gains and the possible costs and then choose
the option with the greatest expectable utility (total amount o chances minus
total amount o risk). It is then perectly conceivable that a reduction in biodi-
versity could be preerable to the status quo; or instance, i reduction means the
elimination o pests which in turn increases the probability o higher yields. Inthe second scenario, we try to calculate the expectation value or human beings
who are on this armer’s land. This case seems to be morally irrelevant because it
is hard to see what the possible benet or possible harm engendered by the loss
o biodiversity could consist o.
I other armer’s arable land is aected, the situation becomes more compli-
cated. What must be taken into account are the possible positive and negative
impacts o a reduction in biodiversity caused by all armers. The same reduction
in biodiversity that could be preerable to the status quo in the case o armer A
ETHICAL REFERENCE SYSTEM TO ASSESS BIODIVERSITY 137
43 This kind o utilitarianism would have to argue that only the pleasure and pain o
human beings (or only the ullment o human desires) counts morally.
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138
(because it has a higher expectation value) might have to be assessed as unde-sirable in the case o armer B because it has a lower expectation value than
the status quo. What utilitarianism requires in such a situation is guring out
which o the ollowing two options is the best (better than the other option i
there are only two). Option 1: the total sum o the expectation value o armer
A and the expectation value o armer B resulting rom the reduction in biodi-
versity. Option 2: the total sum o the expectation value o armer A and the
expectation value o armer B based on the status quo ante. I the expectation
value o option 1 is lower than the expectation value o option 2, the loss o
biodiversity must be judged negatively. In that case, there is a duty to reversethe loss o biodiversity, even i this means that armer A is worse o as a result
(in utilitarianism distributive considerations are irrelevant).
The same procedure has to be applied i we take the environment outside
agriculture into consideration.
9.4 appitin th prpd pprh
As mentioned beore, the ERS is the rst step in a systematic process aiming at the
specication and justication o plausible ethical criteria to valuate environmentalimpacts o GM crops on biodiversity. This step is important in two respects.
1. It lays the systematic oundation or the determination and justication o
the targeted ethical criteria. As pointed out above, the ull development o
these criteria would require choosing the most plausible systematic norma-
tive ethical theory and then applying the respective criteria to the ques-
tion o risk and harm regarding biodiversity. This, however, would be beyond
the scope o this project since this is the most basic systematic question o
normative ethics in general. What can be said, nonetheless, is the ollowing:
Irrespective o which theory turns out to be the most plausible one, all theo-ries share some common ground with regard to the assessment o the risks
associated with GM crops. They all agree – albeit or dierent reasons – that
the commercial use o GM crops can only be allowed i there is sucient
knowledge regarding the risks involved. Deontologists would argue that
this is required because without this knowledge it is not possible to deter-
mine whether the risks exceed the threshold value separating permissible
rom impermissible risks. Utilitarians would argue that without this knowl-
edge, it is not possible to determine whether the expected net benet o an
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agriculture with GM crops (or the net benet o specic GM crops) wouldexceed the expected net benet o an agriculture without GM crops.
Furthermore, they all agree that the current scientic risk knowledge does
not yet suce to justiy the commercial release o GM crops. Given this
knowledge it is still not possible to determine in a suciently reliable
way whether the risks o these crops (especially regarding worst cases)
are above or below the threshold. Nor is it possible to determine whether
the commercial use o (specic) GM crops would lead to an (long term)
increase o the net benet in agriculture (as compared with conventional
agriculture). Thus, they would all plea or more risk research based on thestep-by-step procedure.
2. The ERS may be useul or certain practical purposes. Three are worth
mentioning:
a. By providing regulators with a general orientation grid, the ERS enables
them to see which ethical position they intuitively avor.
b. The ERS helps regulators to question their point o view and to modiy it
accordingly. It also acilitates a better and more refected understanding
o the ethical view(s) enshrined in the law. As a consequence, regula-
tors are better able to communicate their position to the “outside world”(industry, scientic community, media, and public at large).
c. The ERS improves comprehension o certain tensions, or instance
the tension between the two aspects o protection that are essential
or biodiversity: the protection o rare and threatened species on the
one hand, and the unctioning o ecosystem services on the other hand.
These two aspects may lead to dilemmas or decision makers because
the relevant legal regulations are based on two dierent ethical theo-
ries that exclude each other. Biodiversity conservation is usually based
on an ecocentric approach according to which biodiversity is intrinsi-cally valuable (and rarity is valuable in itsel). This implies that espe-
cially rare species are entities that deserve protection irrespective o
their value or ecosystem stability and or human beings. The protec-
tion o ecosystem services is mainly based on an anthropocentric
approach according to which biodiversity is only instrumentally valu-
able, namely, insoar as it is necessary or human well being. I only the
anthropocentric approach were relevant or the legal interpretation o
biodiversity, there would be no tension between the two main aspects
ETHICAL REFERENCE SYSTEM TO ASSESS BIODIVERSITY 139
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RECOMMENDATIONS FOR DECISION-MAKERS 145
10.2 Prttin g
Protection goals as specied by existing legislation are the exclusive starting
point or regulators or a denition o damage. Policy decisions on what ulti-
mately has to be protected are based on the existing legal rameworks. Nearly all
legal rameworks demand the conservation and sustainable use o biodiversity.
However, due to practical and nancial constraints, it is impossible to conserve
all components o biodiversity in the same manner. Hence, one needs to be
able to decide which components o biodiversity deserve particular protection.
Both rom an ethical and rom an ecological point o view, the legislative termsused to describe the protection goal “biodiversity” are too vague to be scien-
tically assessed. To dene scientically measurable characteristics or each
ecological entity deserving protection, we propose to rst dene assessment
endpoints that are an explicit expression o the environmental value that is to
be protected. In a second step, measurement endpoints that represent a meas-
urable ecological characteristic that can be related to the particular assess-
ment endpoint are to be dened. We have specied a matrix listing entities o
biodiversity that need protection as well as criteria that need to be considered
when dening corresponding assessment and measurement endpoints. Thepresented matrix can be used as a tool to structure the dialogue between the
dierent stakeholders, especially between regulators and applicants.
Regulatory authorities need to be aware that setting endpoints will require
balancing competing goals that will be a source o controversy. Biodiversity
conservation, or example, usually ocuses on rare and threatened species,
while restoring ecosystem services necessitates concentrating on ubiquitous
species as a species on the verge o extinction is likely to have less signi-
cant ecological relevance. Similarly, although there is general consensus that
the ecological entities specied by legislation to deserve protection have to berespected (such as Red List species and protected habitats), there is contro-
versy over the necessity to protect “common” species that are not explicitly
listed in the legislation, but that are reduced by common agricultural practices
(such as agricultural weeds that may be an essential part o ood webs in agri-
cultural landscapes contributing to armland biodiversity, but that also reduce
agricultural yield).
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2ND
RecoMMeNDaTIoN
Regulators should actively promote approaches that enable stakeholders to agree on
what deserves protection because it is specically valued. Regulatory authorities can
use our matrix speciying protection goals as well as assessment and measurement
endpoints as a starting point or discussing generic and operational biodiversity
protection goals among all stakeholders o GM plants. The matrix can thereby be
adapted to regional or country specic needs. We recommend that science and
empirical evidence support the discourse about policy goals and indicate what
ecological theories tell us about the relevance o biodiversity.
146
10.3 Thrhd
Using a threshold to dene damage would be an elegant approach as it would
allow more or less unambiguous decisions which represent unacceptable
harm. In principle, every indicator value that would exceed the threshold would
indicate damage. Unortunately, the threshold principle is currently not appli-
cable in practice as the legal rameworks regulating the use o genetic engi-
neering in Switzerland and in the European Union (EU) do not dene specicthreshold values. This is mainly due to the diculty to dene thresholds or
ecological indicators. Ecological thresholds must be evaluated independently
or every single species or species group – a procedure that is usually not
appropriate or regulatory decision-making. With growing ecological experi-
ences on the cultivation o GMOs, thresholds or certain ecological groups may
become available. Nevertheless, one has to recognize that or most ecological
indicators ully operational thresholds will probably rarely be available in the
near uture. These complexities inevitably challenge decision-makers as they
generally have no clearly quantied thresholds that allow them to decide whatrepresents damage.
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3RD
RecoMMeNDaTIoN
In theory, thresholds would be an elegant approach to dene damage as every indi-
cator value that would exceed the threshold would indicate damage. Hence, where
available, ecological thresholds should be used or decision-making. However,
regulators should keep in mind that ecological thresholds are seldom available in
practice as ecological sciences are most oten not able to provide precise threshold
values that would indicate when damage occurs. I thresholds are missing, damage
should be dened by using a baseline approach. The baseline allows one to deter-
mine when a change has to be regarded as a damage without relying on a precise,
xed threshold as the denition o damage is perormed by comparing two dierentstates. The rst state (e.g., the impacts caused by current agricultural management
practices) is thereby indicating what is accepted. Damage occurs i the dierence
between the accepted state and the state to be evaluated is judged to be suciently
large to be adverse.
Note, however, that rom an ethical point o view, this understanding o base-
line is problematic insoar as normatively speaking the baseline should include
criteria o acceptability. What is acceptable and what is actually accepted may, but
must not coincide.
RECOMMENDATIONS FOR DECISION-MAKERS 147
10.4 cmprtiv mnt nd bin
The project showed that generic comparative assessments o dierent agricul-
tural management practices are very complex and dicult to perorm because
the impacts o cropping systems depend on a variety o dierent actors that
can oten only be assessed on a case-by-case basis. It is thereore not possible
to reduce these impacts to one common “currency” that would allow a generic
comparison. This challenges the initial assumption o the project that compar-ative assessments are the only way to allow a coherent evaluation o envi-
ronmental risks o GM crops. Every generic comparison inevitably results in
omitting important details that infuence the character and the magnitude o a
specic environmental impact o a particular technology .
It is important to recognize that regulatory authorities do oten not have
a legal basis or ormal obligation to perorm a comparative assessment as
existing agricultural technologies are evaluated according to dierent regula-
tory rameworks. More precisely, the regulatory ramework or pesticides uses
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4TH RecoMMeNDaTIoN
Future political and legislative processes in Switzerland and in the EU should
attempt to harmonize the legal rameworks regulating GMOs and other agricultural
management practices that serve similar purposes (such as the use o pesticides).
Agricultural technologies should be assessed based on their individual properties
and on their risk or the environment and not just because they have been created
by a specic methodology or technology. Regulators rom dierent authorities
should initiate discussions to create a legal ramework or a ormal process thatallows or a comparative approach in situations where the comparison o technolo-
gies is appropriate and where there is a risk that the same protection goals may be
adversely aected.
148
other evaluation criteria than the one or GMOs. Hence, regulatory authoritiesoten reuse to compare the eects o GM crops to the eects caused by, or
example, pesticides. As regulators are orced to restrict their judgments to
the GM legislation, this leads to the irrational situation that the same envi-
ronmental impacts may be judged dierently depending on what agricultural
management practice caused them. In our opinion, this incoherence is one o
the main reasons or the current paralysis o the regulatory ramework or GM
crops in Switzerland and in the EU.
As long as technologies having similar environmental impacts ace dierent
regulatory regimes, a comparative assessment cannot be perormed and it isimpossible to draw a baseline or regulatory decisions. Baselines (i.e., the compa-
rator which serves as a basis or comparison) are nevertheless essential or deci-
sion-making as they dene what makes a change to be regarded damage. Legally,
the baseline or the evaluation o damage rom GMOs should be set by what is
already regarded representing damage today. I GMOs would be regulated on the
same legal basis as other agricultural management practices such as pesticides,
a comparison would be possible as the baseline would be characterized by those
environmental impacts that are already approved and thus implicitly accepted.
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5TH RecoMMeNDaTIoN
We rmly believe that it is the responsibility o regulatory authorities to ensure that
the approval process o new technologies is coherent and perormed according to
transparent criteria. Regulatory authorities need to provide applicants with precise
operational protection goals and they need to clearly indicate what other relevant
inormation they may need or the evaluation o environmental impacts o GM crops.
Protection goals have to be dened by regulatory authorities in a consensus process
involving all stakeholders as applicants alone cannot address the public and seek
or consensus.
RECOMMENDATIONS FOR DECISION-MAKERS 149
10.5 Wkn th rgutry ytm r GM rp
The legal requirements in Switzerland and in the EU require that risks or
the environment are assessed prior to the approval o GM crops. In order to
assess the saety o GM crops, applicants o new GM crops need clear indica-
tions rom regulatory authorities regarding protection goals (i.e., regarding the
environmental entities to be protected rom damage). Unortunately, regulatory
authorities in Switzerland and in the EU do currently not provide applicants with
sucient inormation on operational protection goals when evaluating environ-
mental risks o GM crops.The GMO regulation in the EU is marked by a poor communication
between applicants and the responsible regulatory authorities. Regulatory
authorities are usually not allowed to communicate with applicants to discuss
scientic questions and other issues relevant or preparing dossiers or the
application o GM crops. The process o communication between regulatory
authorities and applicants is practiced very dierently in other countries such
as Australia, New Zealand, Canada and the U.S., where applicants seek advice
rom regulators at an early stage and during the process o dossier preparation.
These practices clearly allow a more coherent application o the legal rame- work and it would be helpul i such practices would also become accepted in
Switzerland and in the EU.
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ReeReNcesCHAPTER 11
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154
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aNNeX 1: lIsT o
WoRKsHoP PaRTIcIPaNTs
Annexes
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166
aNNeX 1: lIsT o WoRKsHoP PaRTIcIPaNTs
andr Bhmnn (c-nvnr) Ethik im Diskurs
Katzenbachstrasse 192
CH - 8052 Zürich
rnz Bigr (cnvnr)
Agroscope Reckenholz Tänikon Research Station ART
Reckenholstrasse 191
CH - 8046 Zürich
Mrk BhnInstitute Joze Stean
Department o Knowledge Technologies
Jamova 39
SI - 1000 Ljubljana
Jérôm crtt
Laboratoire Sols et Environnement
UMR INPL-INRA 1120
2 av. de Forêt de Haye BP 172
FR - 54505 Vandoeuvre-lès-Nancy
Ynn Dv
European Food Saety Authority
Largo N. Palli 5/A
IT - 43100 Parma
Ptr Dui
Swiss Federal Institute or Forest,
Snow and Landscape Research
Zürcherstrasse 111
CH - 8903 Birmensdor [email protected]
Brbr ekbm
Swedish University o Agricultural Sciences
Department o Entomology
PO Box 7044
SE - 75007 Uppsala
ahim GthmnnFederal Oce o Consumer Protection
and Food Saety (BVL)
Reerat 404, Mauerstrasse 39–42
DE - 10117 Berlin
Mr M.c. Gikn
National Institute or Public Health
and the Environment (RIVM)
P.O. Box 1
NL - 3720 BA Bilthoven
Mtthi Kir
National Committee or Research Ethics
in Science and Technology (NENT)
Prinsensgate 18 - PO Box 522 Sentrum
NO - 0105 Oslo
liij Kdin
Vilnius University
Department o Microbiology and Plant Physiolog
Chiurliono str. 21/27LT - 03127 Vilnius
Juin Kindrrr*
Delt University o Technology
Department o Biotechnology
Julianalaan 67
NL - 2628 BC Delt
Jz Ki
Szent Istvan UniversityPlant Protection Institute
Pater Karoly utca 1
HU - 2100 Gödöllö
Pu Hnning Krgh
University o Aarhus, NERI
Department o Terrestrial Ecology
Vejlsøvej 25
DK - 8600 Silkeborg
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ANNEX 1: LIST OF WORKSHOP PARTICIPANTS 167
* participated in the rst expert workshop;
+ participated in the second workshop
Zjk Kun (es rpprtur)*University o Zagreb
Department o Chemistry
HR - Zagreb
Pr Nin Kudk*
University o Aarhus
Department o Integrated Pest Management
Forsøgsvej 1
DK - 4200 Slagelse
Jui link
Swiss Expert Committee or Biosaety
c/o Federal Oce or the Environment
CH - 3000 Berne
cpr linntd
Norwegian Biotechnology Advisory Board
Rosenkrantz gt. 11 - P.O. Box 522 Sentrum
NO - 0105 Oslo
J Prry*
Oaklands Barn
Lug’s Lane, Broome
UK - Norolk NR35 2HT
annik Pyir*
Monsanto Europe S.A.
Avenue de Tervuren 270–272
BE - 1150 Brussels
an Rybud
Syngenta
Jealott’s Hill International Research Centre
UK - Bracknell RG42 6EY
Ku Ptr Ripp (c-nvnr) +
Ethik im Diskurs
Restelbergstrasse 60
CH - 8044 Zürich
Jörg Rmi* Agroscope Reckenholz Tänikon Research Station ART
Reckenholstrasse 191
CH - 8046 Zürich
Dmtri G. Rupki*
Aristotle University o Thessaloniki
School o Agriculture
Dept. o Genetics and Plant Breeding
GR - 54124 Thessaloniki
oivir snvid (c-nvnr)
Agroscope Reckenholz Tänikon Research Station ART
Reckenholstrasse 191
CH - 8046 Zürich
Jrmy swt
6 The Green, Willingham
UK - Cambridge CB4 5JA
Hn vn Tri*
Archeon
Strandstigen 20 A 4
FIN - 00330 Helsinki
helena.troil@archeon.
stn Win*
Linköping University
Department o Medical and Health Sciences
IHS Campus US
SE - 58183 Linköping
Mih Winzr*
Agroscope Reckenholz Tänikon Research Station ART
Reckenholstrasse 191
CH - 8046 Zürich
ann-Gbri Wut suy
Federal Oce or the Environment (FOEN)
CH - 3000 Bern
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aNNeX 2: WHaT Is RIsK?Annexes
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170
aNNeX 2: WHaT Is RIsK?
Andreas Bachmann and Klaus Peter Rippe, Ethik im Diskurs
Intensive discussions within the project team regarding the conception o risk
have shown that this concept needs to be claried more thoroughly. The main
reason is that the standard approach used in environmental risk assessment to
assess risk as a unction o exposure and hazard must be questioned rom a scien-
tic theoretical point o view as it does not indicate where the aspect o probability,
which is essential or an adequate denition o risk, comes into play. The debate
within the project team on this issue resulted in the ormulation o some prelimi-
nary theses by the two ethicists, Andreas Bachmann and Klaus Peter Rippe, thatmust be provocative to any risk researcher. In the ollowing, we want to present
these theses being ully aware o their provocative and controversial character.
Wht i rik?
Risk as a technical term is characterized as a unction o the extent (or the magni-
tude) and the likelihood (or probability) o harm.44 Both variables – probability and
magnitude o harm – are equally essential. Harm denotes something that should
be evaluated negatively. Thereore, the concept o risk is inherently value laden.
For this reason, determining risks is not a purely scientic issue. At best, empiricalscience can determine the probability o a uture event occurring. It cannot deter-
mine, however, how this act – the act that something will occur with a certain
probability – should be evaluated, i.e., whether it is a risk, that is acceptable or not.
This technical denition o risk must be distinguished rom two nontech-
nical usages. First, in everyday language, the term risk oten only reers to the
probability that harm will occur. The term risk is used in this way, or example,
when we say that there is only a small risk o being killed in a plane crash.
Second, the term risk at times only reers to the possible magnitude o harm.
This is the case, or example, when we say that lung cancer is one o the majorrisks that aect smokers.
It is important to keep in mind that the technical concept o risk always reers
to both, the magnitude and the probability o harm. To give an example: since the
risk o being killed implies a great harm, it can only be considered to be small i
the probability o occurrence o this harm is extremely low.
44 I unction is understood as a product then risk is a product o the probability and the
extent o harm. In other words: risk is an expectation value. The ollowing examplemay illustrate what this means: I in situation a) there is a 1% probability o 10’000
people dying and in situation b) a 50% probability o 200 people dying the risk, i.e.
the expectation value in both cases is 100 dead people. Identical expectation values
should be evaluated identically. This means that i the risk o situation b) is deemed
inacceptable this also applies to the risk o situation a).
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ANNEX 2: WHAT IS RISK? 171
What is the relation between risk and hazard? Hazard is usually denedas the intrinsic ability or the potential o something (an individual being, a
substance, an action, an event etc.) to cause harm. Without hazard, there can be
no harm and thus no risk. In this sense, hazard is a necessary condition o risk;
but it is not an aspect or a component o risk. A toxin, or instance, may have
the intrinsic ability to kill people. However, it becomes a risk only i someone
is exposed to it. I this happens, its potential to cause harm may turn into a real
harm; i.e., there is a certain probability that harm will actually occur.
Every hazardous entity is a source o risks. The hazard, i.e., the harm poten-
tial related to this source exists irrespective o whether anybody is exposed to therisk source.45 A risk, however, emerges only when someone is actually exposed
to the risk source. Thereore, exposure is another necessary condition o risk:
without exposure, there is no risk. Exposure in this sense is a digital concept:
either one is exposed to a risk source or one is not exposed. As long as nobody
is exposed to a potentially lethal toxin, or example, there is no risk since there
is no probability o a harm (death in our example) occurring. In this respect,
the likelihood o being exposed is thereore irrelevant. Those who use the term
“likelihood o exposure” usually reer to a certain percentage o a population
that will presumably be exposed to a hazard. This kind o likelihood, however,
45 Hazard designates the harm potential, i.e., the intrinsic ability to cause harm. It is
thereore completely independent o the probability o harm occurring. For example,
i the harm potential o a big avalanche is greater than the harm potential o a small
avalanche, this means that the big avalanche can – has the intrinsic ability to – cause
more harm than the small one. The ormer could, let us say, lead to the complete
destruction o a protection orest whereas the latter could only lead to a destruction
o a small part o this orest. This hazard exists irrespective o any probability o
the respective harm occurring. Another example may help to urther clariy this
point: Toxic substance A and toxic substance B both have the ability to kill. This is their hazard. The probability that death occurs i a person ingests either o these
substances may vary because substance A is more toxic than substance B. Hence,
it may be true that substance A is more likely to kill this person than substance B.
However, this does not aect the hazard, i.e., the intrinsic ability to cause harm.
Rather, it presupposes the determination o the hazard: Even though both substances
can be deadly (hazard), substance A is more likely to kill a person than – the same
quantity o – substance B. I this is plausible, however, are there not two dierent
hazards relating to these substances? The answer is no because, as ar as the intrinsic
ability to kill individual persons is concerned, substance A and substance B are
identical. In colloquial language, the answer may be dierent. It is completely normal
to say that substance A is more hazardous than substance B, that is, when a person
is exposed to these substances, substance A is more likely to kill this person than the
same quantity o substance B. Thus understood, however, hazard is just another wordor risk (not in a technical sense though, but rather in the everyday sense mentioned
above reerring to the probability that a harm will occur). For this reason, it seems
advisable to orego the concept o hazard altogether and to use the notions o harm
potential and risk instead, the latter being dened as a unction (the product) o
probability and magnitude o harm.
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is not part o the risk itsel. In order to determine a risk, the only relevant actoris the number o individuals (or the percentage o a population) actually being
exposed.46 O course, certain eatures or parameters o exposure may have an
eect on probability. For instance, temporal duration or requency o exposure
(or magnitude o dose) may play a role: the more requent and the longer an
individual or a population is exposed to a risk source, the higher the probability
is o harm occurring. However, this kind o exposure is not equal to the actual
probability. Rather, the connection is inerential insoar as inormation regarding
temporal duration, requency or magnitude o dose can be used to estimate the
likelihood o the occurrence o harm.As shown, neither hazard nor exposure – understood as the bare act o
being exposed to a risk source – is a component o a risk. Yet, in order to deter-
mine a risk, we have to know the hazard (i.e., the intrinsic ability o a risk
source to cause harm) as well as the (approximate) number o individuals or
the percentage o a population actually exposed to this source.47 This knowl-
edge is necessary because without it, the probability and the magnitude o
harm associated with a risk source cannot be determined. However, urther
knowledge is required to determine probability and magnitude o harm. Some
examples – nuclear power plants, avalanches, ecotoxicology – may be useul toclariy this point.
Nur pwr pnt
The hazard o nuclear power plants, that is, their intrinsic ability to cause harm,
is extremely great. Worst case scenarios assume that a core melt accident could
lead to the death o thousands o people. This hazard exists independently o
whether anybody would be harmed by such an accident; that is, it would also
exist i a remotely controlled nuclear power plant was situated in the middle o
a deserted area so that nobody would be killed by a core melt. I this were thecase, nobody would be exposed to this risk source. Consequently, the possible
harm could not turn into a probable harm and there would thus be no risk. In
reality, however, the situation is quite dierent since many atomic power plants
are situated in densely populated areas, which means that countless people are
actually exposed to this risk source. In order to determine the risk or these
46 In many cases, an exact number cannot be ascertained. Thus, the number o
individuals (or the percentage o a population) actually being exposed to a risk sourcemust be estimated. The term “likelihood o exposure” reers to this estimate. I the
exact number (or the exact percentage) cannot be provided, this entails an uncertainty
with regard to the determination o a risk.
47 As mentioned, exposure also comprises aspects such as how much o a substance
someone encounters. This may have an infuence on the probability o a specied
harm occurring.
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ANNEX 2: WHAT IS RISK? 173
people, we have to know the probability and the magnitude o harm. Suppose theprobability o a reactor meltdown accident is 1:33,000 years. Suppose, urther-
more, that the number o dead people (including late atalities) in case o such
an accident amounts to 50,000. Given that quantiable risks can be expressed
in terms o expectation values (i.e., the product o the two variables probability
and magnitude o harm), the risk (the expectation value) amounts to 1.5 dead
persons per year.
A major problem is whether, and i so how, the probability and the magnitude
o harm can be calculated. A purely mathematical calculation is almost never
possible. Usually, the two variables o a risk must be estimated whereby the esti-mates are based on experience and/or model calculations. How these variables
are determined depends on the case at hand.
Regarding the risk o a meltdown accident in a nuclear power plant, the
analysis o the probability component is a complex procedure (Birkhoer, 1980;
Weil, 2002).48 It basically consists o recording the possible accident sequences
induced by an initiating event by means o event trees and then calculating
the probabilities o ailure o the dierent saety systems ultimately leading
to a core melt by means o ault tree analyses using Boolean logic. One prob-
lematic aspect o this approach is that its results are aficted with uncertain-ties resulting rom unveriable assumptions and models. Another problem-
atic aspect is that experts do not agree on the concept o probability. Some o
them avor a subjectivistic probability theory according to which probability is
a measure o degree o belie. Others avor an objectivistic probability theory
according to which probability reers to the relative requency o an event
(Birkhoer, 1980; Weil, 2002).
Depending on the direction in which the radioactive radiation released by a
core melt moves, the magnitude o harm (expressed in lives lost) is great(er) or
small(er). What is thus required or the risk assessment o a Maximum CredibleAccident (MCA) – beyond calculating the probability o a core melt accident – is to
determine the probability o the direction in which the radiation would move in
case o an MCA. MCA reers to the worst possible magnitude o harm (“hazard”):
the greatest number o people possibly harmed (i.e., killed) in the short and
long run by a core melt accident and its associated discharge o radioactivity.
Given the state o scientic knowledge, it is clear that this harm, as well as the
probability o its occurrence, can only be roughly estimated, but not precisely
determined (Niehaus, 1984; Weil, 2002).
48 In the ollowing, only the risks o purely technical ailures are taken into consideration.
We are well aware, however, that other aspects such as human ailure or external
actors (or instance, earthquakes or tsunamis, or a combination o both) are also
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This example highlights that when we are about to perorm a risk assess-ment, we do not only want to know what may or could happen, we want to know
the probability with which it will happen. In our example, we want to know the
probability o a core melt accident occurring and we want to know the probability
o the radioactive radiation released by this accident to harm (kill) the greatest
possible number o people.
This example also shows that risk assessments can be replete with uncer-
tainties regarding the probabilities and the magnitude o harm. These uncer-
tainties limit the accuracy and reliability o risk statements. Hence, they should
be reduced as ar as possible. In many cases, however, it will not be possible tocompletely eliminate them.
avnh
While risks o nuclear power plants are mainly induced by a certain technology,
the risks associated with avalanches may be regarded as primarily induced by
natural processes.49 The ocial scientic terminology (see www.sl.ch) in this
area is muddled as it equates hazard with the probability o an avalanche occur-
ring and risk with potential harm. Both terms are used in a wrong way. Hazard
means the potential o an avalanche to cause harm. The aspect o probability isnot included. And risk is not potential harm, but probable harm. Furthermore,
since risk always contains a harm component, it must not be conounded with
the probability o some event occurring. The use o the risk concept is only
adequate i the event in question must be considered harmul. Avalanches are
only risks thereore, i they threaten individuals (or material assets) that would
be harmed with a certain probability in case they would be triggered.
As ar as the probability o triggering avalanches is concerned, European
avalanche bulletins content themselves with qualitative statements, distin-
guishing between ve levels: low, limited, medium, high and very high. Theselevels are rather vaguely dened. “Low,” or instance, means that due to generally
very stable snow, avalanches triggered by persons are unlikely and conned to
very ew extremely steep slopes. “Very high” means that due to generally unstable
snow, even on gentle slopes, many large spontaneous avalanches are likely to
occur. To reach this degree o precision, a great amount o data and experience is
required. Since avalanches are complex phenomena, even this does not seem to
suce, however, to determine probabilities quantitatively – much less to predict
avalanches with certainty.
49 Even though they can be considerably increased or decreased by human behavior.
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As ar as the hazard o avalanches is concerned, the decisive criterion isavalanche size. There are our sizes: slu, small, medium, large. “Small,” or
example, means that the avalanche can bury, injure or kill a person. “Large”
means that also large trucks and trains as well as large buildings and orest
areas can be buried and destroyed.
Knowing the level o probability and hazard, however, is not sucient to
determine the risks associated with avalanches. The aspect o probability
mentioned above solely reers to the likelihood that avalanches are triggered by
spontaneous events or human activity. The probability o harm remains unknown.
The aspect o hazard solely reers to possible harm, not to probable harm. Whatis lacking is the determination o the probabilities related to the dierent levels
o hazard. For that purpose, the component o exposure needs to be analyzed.
Exposure has two aspects. On the one hand, the aspect o being exposed to a risk
source: i someone is not exposed to an avalanche in the sense that he cannot
possibly be harmed or reasons o spatial distance, there is no corresponding
risk. On the other hand, exposure has characteristics such as temporal duration
or geographical location that aect the probability o being harmed: depending
on the route skiers or climbers choose, or instance, the probability o being
harmed (i.e., injured or killed) by an avalanche is greater or lower. Again, giventhe state o knowledge, these risks can only be determined qualitatively. They
cannot be quantied because neither the probability o being injured or killed
by an avalanche nor the number o persons being exposed can be precisely
(numerically) ascertained.
etxigy
In ecotoxicology, risk is commonly interpreted as a unction o exposure and
hazard. This interpretation is not equivalent to the standard denition o risk
being a unction o probability and magnitude o harm since probability is notthe same as exposure and magnitude o harm is not the same as hazard.
As explicated beore, hazard is the intrinsic ability or the potential o
something – a toxic substance in our case – to cause harm. In other words,
hazard reers to the possible harm such a substance may bring about. Risk
assessments, however, do not aim at determining possible harm. Rather, they
are targeted at determining (more or less) probable harm. To reach this goal,
exposure analysis is the next necessary step. Again, the two aspects o expo-
sure must be careully distinguished. First, there is only a risk i someone is
ANNEX 2: WHAT IS RISK? 175
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176
exposed to the hazardous risk source. Second, every exposure is characterizedby certain properties (exposure actors), such as, temporal duration, requency,
dose, number o individuals exposed etc. These properties must be known in
order to determine the probability o harm. They are, however, neither equal to
the actual probability nor do they suce as such to calculate this probability.
What is also required is a stochastic deliberation refecting the act that there
is not enough causal knowledge or making deterministic predictions.
An example may serve to illustrate how this might work. A population
o 100 sh is exposed to a certain dose o a toxic substance. Within a certain
period o time, 50% o the sh die. This is the harmul eect caused by the toxicsubstance. From this, a stochastic conclusion regarding risks can be drawn
(provided the sample is large enough), namely, the conclusion that the prob-
ability o dying amounts to 50% (under laboratory conditions) or every sh o
a population exposed to this dose o a toxic substance.50
There is an important dierence between the statement ”dose x o a toxin
will lead to the death o 50% o the members o the exposed population” and‚
“there is, ceteris paribus, a 50% probability or each member o the exposed
population to die o dose x o a toxin.” The rst is a prediction based on a cause-
eect-relationship. It states a certainty as opposed to the second statement which expresses a probability implying an uncertainty whether the uture event
actually will take place. The ormer is a deterministic prediction, and the latter
is a probabilistic prediction. The aim o risk assessments are accurate proba-
bilistic predictions. Deterministic predictions by contrast are not part o such
an assessment. I deterministic predictions are possible, we should not speak o
“risk analysis” or “risk assessment.”
This caveat is important or the ollowing reason. Given that we live in a caus-
ally determined world,51 it would be possible to predict any event with certainty
i we knew all relevant causal actors.52 Under such conditions, there would be norisks. The world, however, is so complex that, given the current state o science,
it is impossible in many cases to make reliable predictions based on our knowl-
edge o cause-eect-relationships. In this situation, we have to content ourselves
with probabilistic predictions, especially with regards to complex systems. In
justiying such predictions, three limiting actors play a crucial role:
50 “Every sh” does not reer to the single sh as an individual, but as a member
o a certain sh species.51 I quantum mechanics is true, physical processes at subatomar scales cannot be
explained deterministically. At this level, thereore, only probabilistic predictions
would be possible.
52 Thus, uncertainty is always due to lack o inormation or knowledge. There is no
uncertainty that a possible increase in knowledge could not eventually eliminate,
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• Time axis: Observation periods are usually rather limited. It is thus dicultto predict (in a probabilistic sense) what may happen in the long-term.
• Amount o data: Sucient data or making reliable probability statements
is oten not available. Yet, without sucient data, the risk level cannot be
determined. Given a sample o 100 persons o whom 50 are smokers and 50
are nonsmokers it is not possible to derive any scientically sound statement
regarding the (absolute) risk o lung cancer or smokers in general.
• Causal actors: Laboratory experiments oten do not – or, given the current
state o knowledge, cannot – detect all relevant causal actors. And even i
all relevant causal actors are known, their interaction may be too complexto allow deterministic predictions.
It may be argued that the toxic eects o a substance can be determined
more reliably in the laboratory than in the reality o a complex system because
the causal actors can be controlled more accurately within the laboratory.
However, what we want to know in the end are the eects o the toxin under real
environmental conditions, that is, under conditions in which a whole array o
other actors may infuence the eects o the toxin. These eects are too complex
to be deterministically predicted, or instance, by extrapolating them out o theavailable limited knowledge. At this point, we have to resort to risk analysis, ulti-
mately aiming at scientically sound probabilistic predictions. However, here we
ace yet another problem. In the laboratory, the hazardousness o a toxin can be
ascertained under specic and controlled conditions. In eld trials, the results
achieved in the laboratory can be tested, although only under restricted condi-
tions and or a limited amount o time. At most, eld trials thus enable a more
complex causal analysis. However, this is not enough to make suciently reli-
able risk statements as eld trials cannot generate the amount o data necessary
to make sound probabilistic predictions about eects in complex environmentalsystems. Presumably, the only way to achieve this is to monitor real systems,
whereby “monitoring” means collecting the data required to make well-ounded
probabilistic predictions.
What does this mean with regards to the risk assessment o GMO? It is impor-
tant to note that the approach sketched thus ar is only tenable in this respect i
certain assumptions concerning GMO in general, GM crops in particular prove
to be plausible.53 The basic question is: I a crop such as maize is changed by
inserting a oreign gene into its genome, is the GM maize just the old maize plus
ANNEX 2: WHAT IS RISK? 177
53 The ollowing remarks are owed to critical comments o Alan Raybould on the rst
drat o this chapter.
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the new trait or should it be regarded as a new kind o maize? How one answersthis question has considerable repercussions on environmental risk assessment.
The approach outlined in this chapter builds on the assumption that the trans-
genic maize is a new kind o maize. It cannot be maintained i this maize is just
the old kind with a new trait. What is meant by this dierence and what are the
implications or risk assessment?
Suppose a oreign gene expressing a toxic protein is inserted into a plant.
I this GM plant B is the conventional plant A plus this new trait, that would
entail the ollowing:
• As ar as risks are concerned there is no dierence between plant A andplant B regarding the already known risks o plant A. Hence, i the risks o
plant A are suciently known and deemed to be acceptable, there is no need
or risk tests on plant B.
• Risk tests are only required with regards to the new gene expressing a toxic
protein. This can be done in the laboratory, or instance, in order to examine
the eects o the toxin on non-target organisms. Given that it is clear what is
meant by harm in this context and what needs protecting rom harm (targets
or protection), this allows testing whether the GM crop in question is envi-
ronmentally sae. It can then be argued that it is sae i the likelihood o unac-ceptable harm occurring is minimal. This can be ascertained by exposing the
non-target organisms to a dose o this toxin that is (much) higher than these
organisms will encounter under real conditions. I the toxin even in this case
does not cause any harm that is regarded as inacceptable the GM plant as
a whole can be considered sae (enough). Field trials are thereore not nec-
essary as regulatory authorities may permit commercial-scale cultivation o
the crop without requiring more data.
There are two main objections to this view o the relation between the nature o a GM crop and risk assessment:
• This approach is not a risk model aimed at the determination o risks as the
product o probability and harm. It is a causal model aiming at the detection
o cause-eect-relations. Depending on the dose a toxin has certain impacts
on target and non-target organisms deemed to be positive or negative (or
neutral). These relations between cause and eect can be ascertained in the
laboratory. To ensure that the GM plant is sae (enough), the targets or protec-
tion are exposed to a dose considerably higher than they will be exposed to
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in the eld. I no negative eect is observed, the conclusion is drawn that therisk – the probability o unacceptable harm – is minimal. Only at this point, risk
seems to play a role. However, what risk means is no more than the general
epistemic proviso that we are not inallible and that it cannot be absolutely
ruled out, thereore, we may have overlooked something.54 This, however, is
not what is meant by risk assessment, at least not i risk is dened in terms o
probability and (magnitude o) harm. To be sure, this does not show that the
concept o GM crops underlying this approach is inadequate. It only shows
that this concept is not satisactorily connected to risk assessment, understood
as a genuinely probabilistic approach, but to a causal model which seeks topredict the eects o cultivating (certain) GM crops (or instance, on non-
target organisms). Those in avor o this approach should thereore orego the
concept o risk and use a deterministic, not a probabilistic language.
• A second objection is that conceiving o a GM plant as the conventionally
bred template plus trait X resulting rom genetic modication is inadequate.
A GM plant is not the sum o the original plant’s traits and trait X. It cannot
be ruled out that this trait substantially changes the character o the GM
crop in question due to eects on the genetic level (multiple insertions, dele-
tion, ller DNA) and/or to epigenetic mechanisms (gene silencing, positionaleects, and pleiotropic eects). The question is what this means or risk
assessment. The main point is that the GM crop may not just show unin-
tended but unexpected traits. For this reason, lab tests trying to determine
the risks associated with this crop are o limited signicance. They must be
supplemented by eld trials and by post-market monitoring. At this point,
it is important to emphasize that environmental risk assessment should not
be conceived o as a pragmatic tool or decision-making under conditions
o limited time and money. Rather, its purpose is to generate the scientic
risk knowledge necessary to decide whether the risks associated with GMplants are acceptable or not. Whatever is necessary to ulll this task must be
done – regardless o how long it takes and how much it costs. O course, eld
trials as well as post-market monitoring should be based as ar as possible on
clear risk hypotheses. It does not make sense to collect large amounts o data
i these data do not help improve risk knowledge. Yet, as long as we do not
understand all the environmental actors that could infuence the GM plant
and the interplay between these actors and the structure o the plant eld
trials are necessary. This is so even i it were true that in many or even most
ANNEX 2: WHAT IS RISK? 179
54 In German, this is expressed by the phrase: “mit an Sicherheit grenzender
Wahrscheinlichkeit.”
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cases, the environment mitigates rather than exacerbates potentially harmuleects. One central aim o risk assessment consists precisely o determining
the probability o those – maybe not very common – cases in which harmul
eects are exacerbated and not mitigated by the environment.
Above, an argument was mentioned according to which a GM crop is sae
(enough) i the probability o unacceptable harm occurring is minimal. However,
whether this argument is valid cannot be decided by empirical science since it
concerns a normative question that lies beyond the reach o science: the question
o acceptability. Thus, even i it were true that the risks o GM crops – includingthe risks concerning worst cases – can be ascertained in the laboratory, this
would not entail that the commercial release o a GM crop is admissible i the
likelihood o unacceptable harm is minimal.
As ar as the normative criterion or risk acceptability is concerned, there are
two prominent approaches that reject the idea that activities or technologies that
have the ability to cause inacceptable harm are acceptable, all the same provided
the probability o this harm occurring is minimal.
• The rst approach is based on the maximin or minimax criterion. According
to this criterion, unacceptable harm means harm that must be prevented atall costs. This implies that the likelihood must be zero, whenever possible.
And this, in turn, entails that the respective activity – in our case, the
commercial release o a GM crop – must be prohibited given that this is the
only way to lower the likelihood o the harm occurring to zero. However,
almost zero is not enough.
• The second approach is based on a threshold criterion according to which
risk as the product o probability and magnitude o harm must not exceed
a predened threshold value. This implies that even i the probability o a
harm occurring is extremely low, this per se does not justiy the risk – orrather the activity associated with this risk – because the harm may be so
severe that the risk is still above the threshold.
Regarding some quite well-known GM plants, or example, Bt-maize, one
could argue that by now we do have enough data and knowledge to conclude
that the risks associated with them are so low as to be negligible and there-
ore acceptable. This conclusion can only be valid, however, i the probability
regarding the worst case, i.e., the greatest possible harm, can be determined with
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sucient precision. “Sucient precision” does not require quantitative speci-cation. Qualitative determination may also be acceptable. For this to be the case,
however, one condition must be met: it must be possible to categorize the prob-
ability in a way that allows comparing it to the probabilities o other risks, or
instance, the probability o a strong earthquake – deemed to be low or very low.
Otherwise, it remains too vague, making it impossible to decide whether the
corresponding risk is acceptable or not.55
The same problem arises with regard to unintended eects o GM plants.
In this case, the analysis o worst case scenarios should aim at estimating the
probability with which, or example, pleiotropic and epigenetic eects triggera dynamic that would result in an irrevocable destabilization or even complete
collapse o ecosystem equilibrium. The main problem here is that on the one
hand, it is inadmissible to extrapolate rom the laboratory to the reality o complex
ecological or agricultural systems whose causal actors are scarcely known.56 On
the other hand, it is not possible in this case to derive probabilities o specic
events that have never occurred rom known eects. It is an open question, then,
as to how the probability o a maximum possible harm occurring can be deter-
mined, i it can be determined at all.57 Since this is an important point, it is neces-
sary to take a closer look at the conventional deterministic approach o assessingtoxic risks o GM plants. In our context, the main point to discuss is whether this
approach is able to give due consideration to the aspect o probability.
ANNEX 2: WHAT IS RISK? 181
55 It is oten argued that the risks o a GM crop are acceptable i they are not (signi-
cantly) greater than the risks o its conventional counterpart. This normative argu-
ment is untenable or the ollowing reason. Logically, the act that B (a GM crop) is
not worse than A (the respective non-GM crop) does not make A good or acceptable.
It does not imply anything about the value o A. Even i A were very bad (harmul)
and utterly inacceptable, it would still be true that B is not worse than A. Obviously,
this does not make B acceptable. So this kind o comparison is empty with regard to
the question o the acceptability o B. In other words, it only works i A is acceptable.
However, how do we know that? The point is: Acceptability is a normative concept
that cannot be determined just by looking at legal regulations. There are many legal
regulations o risks that are accepted; and yet the risks regulated are inacceptable.
Acceptability must be logically distinguished rom acceptance. In this sense, it is a
normative or ethical concept. Ultimately, the dierent ethical risk theories provide the
standards or acceptable risks. Thereore, the baseline or acceptability cannot be an
existing legal standard regulating conventional agricultural products. Acceptability
must reer to normative standards that are independent o legal regulations even
though they may happen to be enshrined in the law.
This reers to the worst case scenario outlined above: the collapse o eco systems
resulting rom a dynamic due to pleiotropic or epigenetic eects. The point is simply this: whatever we may be able to test in a lab, it will not suce to allow deriving the
probability o this worst-case occurring. In other words, it will not suce to justiy the
conclusion that the likelihood o the worst-case happening is so low as to be negli-
gible and thus acceptable.
We will come back to this point at the end o this section.
56
57
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A common test o acute toxicity is the LD50 test. In this test, an animalpopulation is exposed to a certain dose o a toxin leading to the death o 50% o
the individuals o this population. The toxic substance is the source o hazard.
Hazard reers to the ability or potential o this substance to bring about a certain
harm – death in the case o LD50. Exposure denotes the act that a population
has been exposed to a hazard over a certain period o time.
LD50 tests are o a deterministic kind. Once the test has established the dose
leading to the death o 50% o the exposed population, it is possible to make
predictions based on this result. These predictions are deterministic – as opposed
to the probabilistic predictions typical o risk assessments: they allow predictinga uture event, namely, that ceteris paribus 50% o a population exposed to a
certain dose o a toxin will die thereo, with certainty because they are based on
the knowledge o cause-eect-relations.
This deterministic approach underlies ecotoxicological tests. Regarding bio-
diversity, or example, the hazard o a stressor on the environment is charac-
terized in the laboratory or under eld conditions using a number o surrogate
species that are thought to be indicative or biodiversity. The intention o the tests
is to determine the (detrimental) eects o the stressor on the species chosen at
given levels o exposure. To this point, this is a purely deterministic proceduredetermining causalities; even though it is commonly called “risk assessment.”
The main question then is how the results o these tests can be transerred
to agricultural systems. Basically, there are two options: either it is justied to
directly transer them or a direct transer is not justied and some intermediate
steps are required.
To justiy a direct transer, the ollowing ontological statement would have to
be true: the same causal actors determine the eects o the stressor – irrespective
o whether we are in the laboratory or in the open system. This implies that there
are no additional – maybe as yet unknown – environmental actors that could infu-
ence the (harmul) eects o the stressor under real conditions. I that were true,
we could, given that we are able to exactly determine the exposure actors, predict
the harm a GM plant would cause once it would be commercially cultivated. There
would be no need to draw upon probabilities below one and above zero as the
probability actor would be one or zero. Probability one means it is 100% certain
that x will occur. Probability zero means it is 100% certain that x will not occur.
The aspect o uncertainty regarding the occurrence o harm would not exist, and
thereore there would be no risks since uncertainty is essential or any risk.
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In this context, the proponents o the deterministic approach argue thatenvironmental risk assessment is basically an extrapolation o the results o the
hazard characterization and the exposure assessment perormed. Extrapola-
tion, however, is an ambiguous notion. For instance, i a vehicle covers a distance
o 200 meters in 12 seconds and 1000 meters in 60 seconds, one can extrapolate
that in 90 seconds it would cover 1500 meters. Understood as a prediction, this
is true i the speed o this vehicle is not infuenced (i.e., changed) by any addi-
tional internal or external causal actors. In that case, extrapolation enables a
kind o deterministic prediction. This, however, presupposes that we know all the
relevant causal actors. Otherwise, the extrapolation is aficted with uncertainty and we have to resort to a probabilistic analysis. In that case, extrapolation only
allows probabilistic predictions.
Applied to the assessment o GM crops, this means that an extrapolation
in the deterministic sense is only possible i 1) all causal actors relevant in
view o the possible harm caused by these crops and active under laboratory as
well as real conditions are known; and i 2) these causal actors are identical. I
conditions 1 and 2 are met, we should avoid speaking o risks and risk assess-
ment since risks essentially imply uncertainty. I conditions 1 and 2 are not met,
we should avoid speaking o a “deterministic approach” in the context o riskassessment and use the term “probabilistic approach” instead.
Given the current state o scientic knowledge, it is more plausible to
understand extrapolation in a probabilistic sense. The main reason is that, as
mentioned beore, we do not know all causal actors possibly relevant under
the environmental conditions o open agricultural systems and thereore
cannot transer laboratory results or results o eld trials directly to these
systems. In other words: it cannot be ruled out that the eects o GM crops
within these systems are shaped by infuencing actors we do not know. That is
why or the time being, sae deterministic predictions regarding these eectsare out o reach.58
The deterministic approach does not seem to be able to take the aspect
o probability adequately into account. This is no surprise as the approach is
geared to causal analysis, allowing reliable deterministic predictions based on
cause-eect relationships. In this approach, there is no room or uncertainties
ANNEX 2: WHAT IS RISK? 183
58 Accurate probabilistic predictions concerning the risks o GM crops also require causal
knowledge, without, however, being reducible to this knowledge. It is important to notethat causal knowledge is not always necessary. The lung cancer risk o smokers, or
instance, can be probabilistically predicted on the basis o statistical knowledge alone.
Statistical knowledge does not presuppose causal knowledge: even i one has no clue
regarding the causal connection between smoking and lung cancer one can make an
accurate probabilistic prediction.
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and thus or probabilities except probability = 1 (100%) or 0 (0%). The proba-bilistic approach seems better suited to handle the uncertainties we are aced
with due to a lack o causal knowledge.59
The main diculties concerning the calculation or estimation o prob-
abilities have already been mentioned. In conclusion, it may be helpul to list
them once again:
• In order to reach sound stochastic conclusions about possible harmul
eects in complex environmental systems, a large amount o data is required.
A good example to illustrate this point is meteorology. Weather orecasts
are probabilistic predictions. They are probabilistic because the weathersystem is too complex and too dynamic to allow deterministic predictions,
at least given the current state o meteorological knowledge. In order to
make probabilistically accurate orecasts, two things are needed: rst large
amounts o (relevant) weather data; and second, probability calculations.
Good weather orecasts are thus based on enough data-based inormation
on one hand, and on the other hand, on meteorological and mathematical
knowledge backed by sucient computing capacity.60
What would adhering to a probabilistic risk approach mean with regard
to environmental risk assessment in the area o GM crops? Given that agri-cultural systems are as complex and dynamic as weather systems, and given
that a GM plant is a new kind o plant and not just the old plant plus the
new trait, the ollowing conclusion can be drawn: a ull-fedged scientic
risk analysis necessitates a) a large amount o (relevant) data that cannot
be accumulated by a laboratory experiment or even a eld trial restricted
to a ew sampling sites, but only by monitoring real large-scale agricultural
systems where GM crops are cultivated; and b) ecological and mathemat-
ical knowledge backed up by sucient computing capacity.
59 It is important to distinguish between two dierent risk-related uncertainties.
1) The uncertainty regarding a uture event happening; 2) Uncertainties regarding
the determination o a risk. To give an example, when a person plays Russian
Roulette, there is a probability o 1 in 6 that this person will be killed by a pistol
bullet. Thus, regarding the determination o the risk, there is no uncertainty since
the probability can be mathematically calculated and the possible extent o harm
is unequivocally clear (provided that death is harm). This does not detract rom the
act, however, that it remains uncertain whether this person will die. In this respect,
only a probabilistic prediction is possible since we do not have the causal knowl-
edge required or a (justied true) deterministic prediction.
60 This does not mean that scientic weather orecasts are necessarily more precise
than orecasts made by “weather prophets” who base their predictions on subjective
experience and historical knowledge. Yet, it is beyond reasonable doubt that scientic
orecasts are incomparably more reliable and trustworthy than orecasts made by
lay people. The reason is that they are grounded in a much better understanding o
the weather system, understood as “deterministic chaos.”
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• In view o unintended (and unexpected61
) eects o GM plants, the proba-bilistic approach is aced with a dierent problem when it comes to esti-
mating the probability o the worst case scenario occurring. The problem
is, we cannot directly iner the probability o this worst case on the basis o
known eects.
Thus ar, we have outlined the problems to be overcome when trying to calcu-
late probabilities with regard to the risks associated with GM crops. It has not
been made suciently clear, however, which methods may help to solve these
problems. The remainder o this chapter will be devoted to this topic.The question to be answered is: how can statements such as, “The prob-
ability o harming non-target organisms by commercially cultivating Bt-maize
is (very) high/ (very) low (or alternatively, is x%)” or “The probability o a
complete collapse o ecosystem equilibrium (harm) caused by pleiotropic and
epigenetic eects is (very) high/ (very) low (or, alternatively, is x%)” be justi-
ed? What methods can be used in order to calculate or at least reasonably
estimate these probabilities?
MethodsThe standard ormula o the classical conception o probability is
.
That is, probability p regarding event E is equal to the ratio o the number
o avorable cases N(E) to that o all the cases possible N.
This ormula allows calculating probabilities quantitatively in two kinds
o cases:
• In cases where physical conditions are irrelevant and p can be calculatedpurely mathematically (lottery 62)
ANNEX 2: WHAT IS RISK? 185
61 Insoar as unexpected (and maybe even unexpectable) eects result rom the
dynamic and complex interplay between the GM plant and the open agricultural
system, they can only be detected by monitoring this system. O course, they must
rst maniest themselves beore one can start thinking about the risks associated
with them.
62
The probability o getting the correct six numbers in lottery 6/49 is 1/14 million. Thisprobability is calculated by means o mathematics alone. This probability means
that getting six right is extremely unlikely – irrespective o the number o players
taking part in the lottery. However, the more players there are, the greater is the
probability that one o them will win. The same event whose occurrence is extremely
unlikely or each player becomes very likely (weak law o large numbers).
p(E) = N(E)
N
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• In cases where the calculation o p can be based on physical symmetries (aircoin, air die, roulette etc.63).
I there is no physical symmetry, as in the case o GM crops, the method
o the classical conception cannot be applied. At this point, the method o the
requency account comes into play. This method is also based on the ormula o
the classical conception since the requency conception is, structurally speaking,
the a posteriori version o the classical conception: ”it gives equal weight to each
member o a set o events, simply counting how many o them are ‘avorable’ as
a proportion o the total. The crucial dierence, however, is that where the clas-sical interpretation counted all possible outcomes o a given experiment, nite
requentism counts actual outcomes” (Hajek, 2009).
I, or instance, an asymmetrical die is biased in avor o number our, the
appropriate way to nd out the probability o this number occurring is to conduct
a suciently long series o throws in order to ascertain p via relative requency.
In other words: in empirical cases like these, what is needed to ascertain p are
the data required to determine relative requency in a reliable manner since this
requency is (approximately) equal to p.64 Suppose, or instance, a parachutist
worries about the saety o his two parachutes. He wants to know the probability that neither o them will open. In order to calculate this probability, we have to
know the probability o each parachute not to open. This is something we can
know only a posteriori, that is, based on experiences made with this product.
Suppose it is known that the parachute opens in 999 o 1000 cases. Thus, p(E
not open) would be 1/1000. I this applies to both parachutes, the probability we
are looking or would be 1/1000 x 1/1000 = 1/1,000,000 (using the rule o multi-
plication). Statistically speaking, this means that in one in a million cases, both
parachutes remain closed.
How do we nd out that the parachutes in question open in 999 o 1000cases? The answer given is by experience. In this context “experience” has
dierent aspects. 1) Parachutes are a ully developed technology. Thus, i
someone constructs a new parachute, it is possible to derive some conclu-
sions regarding the probability o it not unctioning based on the accumulated
63 Physical symmetry is never completely perect and hence always a kind o idealization.
Yet it makes sense to suppose its existence in these cases since it allows calculating p
accurately enough or practical purposes. This also applies in the case o the air coin
even though the result p=1/2 does not take into account the possibility o the coin
landing “edge.”
64 In case p is known, it is very likely according to the law o large numbers that the
proportion o avourable events, (i.e., the relative requency), will be approximately
equal to p.
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knowledge o parachute technology. 2) Tests perormed beore market launch 3).Monitoring o the product ater market launch. Since the technology is already
ully developed, 1) and 2) are presumably sucient to come to a plausible esti-
mate o p (provided the new parachute is not revolutionary). However, the exact
probability can only be ascertained by collecting enough data ater market
launch to produce reliable statistics based on relative requency.
Basically, this approach is applicable in a wide range o cases, especially
cases belonging to the realm o the natural sciences. Take meteorology once
again as an example. What is meant by a orecast statement such as, “There is
a 30% probability o rain tomorrow?” It means, there is rain on 30% o all thedays characterized by the same (or similar) weather conditions as tomorrow.
“Tomorrow” here does not reer to a single event, but to an instance o a type.
In order to be correct, the orecast presupposes a quantity o data large enough
to acilitate reliable statistical statements concerning the probability o rain
under conditions dened by variables such as air pressure, cloud types, and
temperature.
Regarding natural events, the problem o determining the probability o
single cases is oten not as urgent as it may seem. O course, we want to know
how the weather will be like tomorrow. Thus, we reer to a single case: a uniqueuture event (there is only one tomorrow). It is true that the method o rela-
tive requency is unable to assign probabilities to single cases. However, this
does not imply that there is always a relevant dierence between statistical
probabilities and single case probabilities. Regarding the weather orecast, the
dierence between tomorrow as a single case, a token, and tomorrow as an
instance o a type may be negligible since the relevant variables may enable
quite specic probabilistic predictions so that single case and instance o a type
practically coincide.
This may be dierent when we consider, or instance, probabilities pertainingto the lie o a particular individual. Consider, or example, customer proles
used by insurances to calculate the lie risk o their clients. According to the
requency conception, insurances should take into account all variables that may
have an impact on lie expectancy such as age, sex, and health. The more vari-
ables being used, the more individualized the corresponding probability state-
ment. Nonetheless, the probability is only an approximation to an individual case
since its calculation is based on the principle that the narrowest (most speci-
ed) reerence class or which reliable statistics is available should be chosen.
ANNEX 2: WHAT IS RISK? 187
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Again, this does not necessarily mean that there are practically relevant dier-ences between this probability and the probability o the single case. Intuitively,
however, there may be such dierences. Thereore, the question arises o how
probabilities pertaining to individual persons can be determined.
Imagine the ollowing case (Gillies, 2000): Mr. Miller, 60 years old, has been
smoking three packets o cigarettes per day or thirty years. What is the prob-
ability that he will live until the age o 70? Suppose there is a reliable statistics
or these kinds o cases. The probability o Mr. Miller living until the age o 70 is
the requency o those in this class who have lived until the age o 70. It seems
reasonable, however, to adjust this probability i we learn that Mr. Miller comesrom a very large amily who all smoke three packets o cigarettes per day, but
none o whom died beore the age o 70. The question is, how much would the
probability change i there were no statistical data available concerning indi-
viduals who belong to such unusual amilies? In this case, we seem to be orced
to resort to a rather subjective and vague estimate.65
However, the probability regarding adverse eects o (specic) GM crops on
biodiversity is primarily a statistical, not a single case probability. From a meth-
odological viewpoint, this means that this probability should be determined by
means o the requentist approach. This approach is based on experience. Inthe case o GM crops, experience comprises the same aspects as in the para-
chute example: 1) Conclusions regarding p that are based on the knowledge
we already have. 2) Tests beore commercialization o GM crops (in the labora-
tory; eld trials); 3) Monitoring ater market launch. The main questions to be
answered are: what kind o and how much inormation do we need to derive
statistically valid probabilistic conclusions? And, how do we get this inorma-
tion? Some o the diculties in answering these questions have already been
mentioned. In light o the methodological deliberations just made, one di-
culty regarding the quality o the data required can be ormulated more clearly.The requentist method is a quantitative method. It is based on the idea that
probability can and must be determined quantitatively. This does not neces-
sarily imply that every probability must be expressed by an exact number.
It may also be the case that we can only speciy a particular range. Maybe
the probability o an event is above 1% and below 10%. And within that band,
65 In some cases, the best method to use in order to estimate singular probabilities may
be Bayes’ rule. This rule allows adjusting subjective probabilities in a controlled way inthe light o new experience. However, in most cases, the data resulting rom the new
experience can also be interpreted objectively (i.e., in a requentist manner) by orming
appropriate reerence classes. Bayes’ rule is to be avored only in cases where we have
good reasons to assume that there is a practically relevant dierence between type-
and token-probability.
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it is impossible to assign probabilities. However, what about qualitative prob-ability statements? One might think that according to requentism, such state-
ments cannot be scientically sound and are thereore inadmissible. However,
we could also argue that qualitative characterizations o probabilities such as
“low” or “high” can be acceptable, provided that they are not completely arbi-
trary. However, this only makes sense i they are implicitly connected in some
way to numbers. On the one hand, we have here a conventional element: to call
a probability o 40% low is not plausible given the way we use the word “low”
in this context. On the other hand, qualitative characterizations may reer to
an approximate range within which they cannot be exactly localized. I noteven such a range can be determined, possible qualitative probability state-
ments remain vague. They are then expressions o subjective belies that are
not intersubjectively justiable.
Given a liberal understanding o the requentist method, it may, in the
sense just indicated, be admissible to estimate probabilities even i this
only allows qualitative characterizations. One should be aware, however,
that this becomes problematic i one wants to know the probability o the
greatest possible harm occurring (worst case). Take nuclear power plants as
an example. In this case, the probability o the worst case cannot be derivedrom experience in the sense discussed above. There has hardly been any
Maximum Credible Accidents (MCA). So it is not possible to produce a reli-
able statistics in the sense o relative requency. There is, however, another
option, namely, probabilities can be determined sequentially. As pointed out
beore, this is done by a complex component analysis. The probabilities o a
malunction o the dierent saety systems are calculated and then multiplied
(Weil, 2002). This presupposes that these probabilities can be determined at
least approximately. And this, in turn, presupposes enough experience with
the specic technologies being used. I such an analytical procedure is notapplicable due to lack o experience regarding these specic technologies,
then a worst case probability cannot be derived rom probabilities associated
with known eects. In this case, the only remaining option is to base probabil-
ities on model assumptions or scenarios. This may still allow an approximate
preliminary calculation o the overall probability. The more assumptions that
have to be made, however, the greater is the uncertainty concerning this prob-
ability, until a point is reached where probability statements become so vague as
to be virtually empty and useless.
ANNEX 2: WHAT IS RISK? 189
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The question regarding GM crops is whether there is any way in which plau-sible probabilities o worst-case scenarios can be determined. Since in scenarios
o this kind, GM crops as complex biological organisms are situated in complex
ecosystems whose behavior in many respects is scarcely known, a component
analysis is not possible. This means that these probabilities cannot be derived
(extrapolated) rom known eects and their probabilities. The only option seems
to be to operate with scenarios that are based on knowledge and on assumptions
that have not been scientically veried. Whether this allows determining the
probabilities o worst cases with the precision minimally required is a question
that needs urther consideration.
190
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The debate on the possible impact o genetically modifed (GM) crops on biodiversity shows that so ar
there is no consensus on generally accepted assessment criteria or environmental harm. This debate
stems primarily not rom a shortage o data, but rather rom the absence o criteria or assessing the
eects o GM plants on biodiversity. Since there are no exact assessment criteria, regulatory decision-
making processes are oten not transparent and can be difcult to understand. This increases the
danger that decisions on environmental risks rom GM plants may appear arbitrary.
The VERDI Project (Valuating environmental impacts o genetically modifed crops – ecological and
ethical criteria or regulatory decision-making) is a interdisciplinary collaboration between biosaety
experts and risk ethicists. Its aim is to develop recommendations or decision makers and regulatory
authorities, thus helping to improve the regulation o GM plants. The results show that both the
unambiguous description o protection goals and the establishment o a basis o comparison are
two essential criteria when defning harm.
The book presents a proposal how criteria or the evaluation o GM crops could be developed. The
b k i di d ll h i l d i h d b b f d i k i i i