This document discusses the importance of problem formulation in ecological risk assessment (ERA) for genetically modified (GM) crops. It notes that ERA and ecological research have different goals, with ERA aiming to predict no harm rather than make discoveries. Proper problem formulation in ERA involves considering legislation, the risk analysis process, risk context, and protection goals to identify only credible risks. This ensures the ERA focuses on relevant data and regulatory decisions can be made with certainty. The document provides examples of risk scenarios and contextual factors to consider in ERA for GM cotton and canola. It stresses the importance of data quality, sufficiency and relevance for credible ERA conclusions.

1. ERA vs ECOLOGICAL RESEARCH
The importance
of
a good problem formulation
Dr Joe Smith

2. DIVERSE CROPS / TRAITS
Drought tolerance Insect resistance
Salt tolerance Water use efficiency
Altered starch Nitrogen use efficiency
Enhanced nutrition Disease resistance
Altered oil content Fungal resistance
Improved fibre Sugar content
Herbicide tolerance

3. OUTLINE
 ERA Vs ecological research
 Problem formulation
What is it?
Key factors
Role in risk assessment process
 What data do we really need to know?
Sufficient, relevant and credible

4. ERA ≠ ECOLOGICAL RESEARCH
Both address problems and test hypotheses
BUT
Different problem selection
Different types of hypotheses
Different testing of hypotheses
Confusion ineffective ERA & inadequate research
[Raybould 2008, 2010]
≠

5. ERA ≠ ECOLOGICAL RESEARCH
Research
• Problem - objective
(from analysis of prior problems)
• Hypotheses - interesting
(make precise predictions)
• Testing - aims to falsify
hypothesis
(corroborated by presence of
phenomena in field studies)
ERA
• Problem - subjective
(from definitions of harm)
• Hypotheses - useful
(predict no harm)
• Testing - aims to falsify
hypothesis
(corroborated by absence of
phenomena in lab studies)
[Raybould 2008, 2010]
Essential to have clearly defined problem so that risk assessors can
conclude with some certainty that particular harms will not eventuate

6. PROBLEM FORMULATION
WHAT IS IT?
‘…the first step in ERA where policy goals, scope,
assessment endpoints, and methodology are distilled
to an explicitly stated problem and approach for
analysis’
• Improved consistency and focus of ERAs
• Enhances relevance and utility for regulatory
decision-making
[Wolt et al, 2010]

7. PROBLEM FORMULATION
KEY FACTORS
 Legislation / regulations
 Risk analysis process
 Risk context
 Protection goals – specific harms
 Identify risks that genuinely need further analysis
 Remove hypothetical or negligible risks
‘The formulation of a problem is often more important than its solution’
(Albert Einstein)

8. LEGISLATION AND REGULATIONS
 The government mandate
 Reflects community values, expectations
 Responsibilities for decisions
 Scope, definitions
 High level regulatory criteria

9. RISK ANALYSIS PROCESS
INCORPORATING PROBLEM FORMULATION
[Wolt et al, 2010]

10. RISK CONTEXT
Critical factor in framing the risk assessment, problem
formulation and determining what we need to know

11. • Canola parent (B napus) – exotic, annual/biennial, natural toxicants,
weed in agricultural but not undisturbed habitats
• Activities – as for commercial non-GM canola; widespread cultivation
for oil, meal production
• Traits - herbicide tolerance
 increased competitiveness in presence of herbicides
• Receiving environment – biotic and abiotic factors,
agricultural practices, related plants, related proteins
• Previous releases – field trials, commercial, overseas
CONTEXT FOR HT CANOLA
[Commercial release]
Source: OGTR

12. • Expect few identified risks because of proposed limits and
controls
• Measures to limit and control release:
 Separate trial sites – pollen traps or isolation zones
 Harvest trial plants separately
 Clean equipment, destroy unused plant material
 Monitor site, destroy volunteer plants
 Regulator’s Guidelines for transport
 No use for human or animal feed
CONTEXT FOR FIELD TRIALS
Source: OGTR

13. • Define assessment endpoints
• Identify characteristics of GM plants with potential to
cause adverse effects
• Postulate exposure pathways for these adverse effects to
occur
• Outline specific risk hypotheses to guide data generation
and evaluation
• Develop conceptual model (pathways to harm) and
analysis plan
FORMULATING
THE
PROBLEM

14. RISK CONTEXT
Activities with
GM crop
Harm to people
or environment
Risk Scenario = plausible pathway to harm
Source: OGTR

15. EXAMPLE FOR COTTON
ACTIVITY
GM cotton
containing
Bt gene
HARM
Reduced
plant
biodiversity
in protected
area
Risk Scenario = plausible pathway to harm
Loss of GM
seed during
transport
Establishment
of GM cotton
near native
cotton
Gene flow
from GM to
native cotton
Increased
weediness
of native
cotton
Source: OGTR

16. DATA QUALITY, SUFFICIENCY & RELEVANCE
 What is the quality of evidence ?
 Is the data available relevant and sufficient?
 What uncertainty is there with the estimate of risk ?
 Is uncertainty relevant or important ?

17. CONCLUSIONS
• Regulatory risk analysis is not research – it is a structured mechanism
for making effective and timely decisions using available information
and taking account of uncertainty
• Problem formulation is critical in ensuring the ERA considers only
relevant and credible risks and is useful for decision-making
• Potential harms, assessment endpoints and credible pathways to the
harms need to be clearly identified at the beginning of the ERA
• Problem formulation helps ensure that data used in ERA of GM crops
is relevant to the questions that need to be answered
• Credibility, quality and relevance of data is essential

18. ACKNOWLEDGEMENT
The views expressed in this presentation are my personal
views alone and not those of any government agency. They
are derived in large part from my experiences as Australia’s
Gene Technology Regulator and I remain indebted to the
outstanding staff of the Office of the Gene Technology
Regulator.