Wednesday 23nd November 2016 - Conference
Track 1: Environmental Risk (Chair: Tom Beer)
Regulatory science versus research science: decision making for environmental release of Genetically Modified (GM) plants.
Keywords: Risk assessment, regulatory science, GM plants, decision making
Author: Dr Alison Wardrop
Affiliation: Office of the Gene Technology Regulator
Email address: alison.wardrop@health.gov.au
Lay summary:
In Australia, the Gene Technology Regulator is responsible for conducting risk analysis for any intentional release of a GMO into the environment. The risk assessments are used for decision making and must be supported by sound science. However, there are differences in approach between “regulatory science” and “research science” and these will be discussed in this paper.
Abstract:
In Australia, the Gene Technology Regulator (GTR) is responsible for conducting human health and environmental risk assessments for intentional release of GM plants. The Regulator’s decisions on whether to authorise the release of a GM plant under the Gene Technology Act 2000 must be based on an assessment of whether any risks to people or the environment can be managed. Sound science underpins the Regulator’s risk analyses. However, in this context it is useful to distinguish between “regulatory science” and “research science.
Research science applies scientific method to understanding a physical or biological system, often directed to furthering knowledge. Timeframes may be open-ended, and uncertainty may be addressed through generation of additional data to increase understanding. In regulatory science, the scientific method is used for the purpose of making a decision about whether to allow something to be used, or activities to be undertaken, within defined legislative framework and timeframes. Decisions are based on analysis and interpretation of scientific knowledge and, where necessary, assumptions to address data gaps or uncertainty.
There are a variety of ways to address uncertainty in a regulatory context. Collecting more data is one way, but it is not always necessary, practical or efficient. Other ways include assumption, eg a worst-case scenario type of assumption, and application of risk treatment/management measures. Importantly, in regulatory science there should be some analysis of the nature, sources and significance of uncertainty and its impact on the decision that needs to be made.
This difference in perspective can lead to confusion between regulators and research scientists or applicants around the type of data required for risk assessment. The practical approach taken by the Office of the Gene Technology Regulator (OGTR) to conducting risk assessments, preparing risk management plans and setting license conditions is explained in the Risk Analysis Framework (RAF), a document developed within the office to inform and guide the risk assessment process. The way in which the office considers the quantity and quality of evidence used in risk identification and characterisation can broadly be described as a weight-of-evidence approach.
The OGTR has recently reviewed the quality, amount and type of data needed to perform an effective risk assessment for environmental release of GM plants. This has resulted in a focused revision of the application forms for intentional release of GM plants into the environment. This paper will explore aspects of the distinction between regulatory and research science, with particular reference to data requirements for risk assessment of GM plants.
In Australia, the Gene Technology Regulator is responsible for conducting risk analysis for any intentional release of a GMO into the environment. The risk assessments are used for decision making and must be supported by sound science. However, there are differences in approach between “regulatory science” and “research science” and these will be discussed in this paper.
Abstract:
In Australia, the Gene Technology Regulator (GTR) is responsible for conducting human health and environmental risk assessments for intentional release of GM plants. The Regulator’s decisions on whether to authorise the release of a GM plant under the Gene Technology Act 2000 must be based on an assessment of whether any risks to people or the environment can be managed. Sound science underpins the Regulator’s risk analyses. However, in this context it is useful to distinguish between “regulatory science” and “research science.
Research science applies scientific method to understanding a physical or biological system, often directed to furthering knowledge. Timeframes may be open-ended, and uncertainty may be addressed through generation of additional data to increase understanding. In regulatory science, the scientific method is used for the purpose of making a decision about whether to allow something to be used, or activities to be undertaken, within defined legislative framework and timeframes. Decisions are based on analysis and interpretation of scientific knowledge and, where necessary, assumptions to address data gaps or uncertainty.
There are a variety of ways to address uncertainty in a regulatory context. Collecting more data is one way, but it is not always necessary, practical or efficient. Other ways include assumption, eg a worst-case scenario type of assumption, and application of risk treatment/management measures. Importantly, in regulatory science there should be some analysis of the nature, sources and significance of uncertainty and its impact on the decision that needs to be made.
This difference in perspective can lead to confusion between regulators and research scientists or applicants around the type of data required for risk assessment. The practical approach taken by the Office of the Gene Technology Regulator (OGTR) to conducting risk assessments, preparing risk management plans and setting license conditions is explained in the Risk Analysis Framework (RAF), a document developed within the office to inform and guide the risk assessment process. The way in which the office considers the quantity and quality of evidence used in risk identification and characterisation can broadly be described as a weight-of-evidence approach.
The OGTR has recently reviewed the quality, amount and type of data needed to perform an effective risk assessment for environmental release of GM plants. This has resulted in a focused revision of the application forms for intentional release of GM plants into the environment. This paper will explore aspects of the distinction between regulatory and research science, with particular reference to data requirements for risk assessment of GM plants.
New Developments in USEPA Science Assessments
Keywords: science assessment, causal, health, ecological
Author: Dr Mary A. Ross
Affiliation: National Center for Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC, USA.
Email address: Ross.mary@epa.gov
Lay summary:
The National Center for Environmental Assessment (NCEA) in the Office of Research and Development occupies a critical position in the U.S. Environmental Protection Agency (USEPA) has a unique and essential role in integrating and synthesizing findings from large bodies of evidence to develop scientific assessments, translating research and communicating scientific findings to inform USEPA decisions, and conducting research and analyses to advance assessment methods. The NCEA program covers a broad array of issues for health, ecological and environmental effects and this presentation describe new developments underway and examples of how they have been implemented in health or ecological assessments.
Abstract:
The National Center for Environmental Assessment (NCEA) in the Office of Research and Development occupies a critical position in the U.S. Environmental Protection Agency (USEPA), by providing scientific assessments of environmental pollutants that support regulatory decisions and policies for USEPA’s program offices and regions. NCEA has a unique and essential role in integrating and synthesizing findings from large bodies of evidence to develop scientific assessments, translating research and communicating scientific findings to inform USEPA decisions, and conducting research and analyses to advance assessment methods. The NCEA program includes the Integrated Risk Information System (IRIS) program that develops high-quality evidence-based assessments of hundreds of chemical agents present in the environment, the Integrated Science Assessments that support the review of the air quality standards for the criteria air pollutants (e.g., ozone, particulate matter), major environmental assessments such as the Hydraulic Fracturing Drinking Water Assessment or Mountaintop Mining, and an ecological causal assessment program. Further, NCEA develops new approaches to ensure that assessment work is systematic and rigorous, incorporating comprehensive literature searches, evaluation of study quality, systematic review of evidence, and structured integration of evidence to derive scientific conclusions regarding the weight of the evidence or causality. The developments underway and examples of how they have been implemented in health or ecological assessments will be presented.
Disclaimer: The views expressed are those of the author and do not necessarily reflect the views or policies of the US EPA.
The National Center for Environmental Assessment (NCEA) in the Office of Research and Development occupies a critical position in the U.S. Environmental Protection Agency (USEPA) has a unique and essential role in integrating and synthesizing findings from large bodies of evidence to develop scientific assessments, translating research and communicating scientific findings to inform USEPA decisions, and conducting research and analyses to advance assessment methods. The NCEA program covers a broad array of issues for health, ecological and environmental effects and this presentation describe new developments underway and examples of how they have been implemented in health or ecological assessments.
Abstract:
The National Center for Environmental Assessment (NCEA) in the Office of Research and Development occupies a critical position in the U.S. Environmental Protection Agency (USEPA), by providing scientific assessments of environmental pollutants that support regulatory decisions and policies for USEPA’s program offices and regions. NCEA has a unique and essential role in integrating and synthesizing findings from large bodies of evidence to develop scientific assessments, translating research and communicating scientific findings to inform USEPA decisions, and conducting research and analyses to advance assessment methods. The NCEA program includes the Integrated Risk Information System (IRIS) program that develops high-quality evidence-based assessments of hundreds of chemical agents present in the environment, the Integrated Science Assessments that support the review of the air quality standards for the criteria air pollutants (e.g., ozone, particulate matter), major environmental assessments such as the Hydraulic Fracturing Drinking Water Assessment or Mountaintop Mining, and an ecological causal assessment program. Further, NCEA develops new approaches to ensure that assessment work is systematic and rigorous, incorporating comprehensive literature searches, evaluation of study quality, systematic review of evidence, and structured integration of evidence to derive scientific conclusions regarding the weight of the evidence or causality. The developments underway and examples of how they have been implemented in health or ecological assessments will be presented.
Disclaimer: The views expressed are those of the author and do not necessarily reflect the views or policies of the US EPA.
Development of a generic risk analysis framework for organisms
Keywords: regulation, environmental risk assessment, genetically modified organisms, biological risk factors
Author: Dr Peter Thygesen
Affiliation: Office of the Gene Technology Regulator
Email address: peter.thygesen@health.gov.au
Lay summary:
In Australia, the Office of the Gene Technology Regulator (OGTR) regulates GMOs to protect human health and the environment, and the regulation is based on environmental risk assessment (ERA). Although there are different types of GMOs, they are all organisms. OGTR has developed a generic risk analysis framework for organisms (GRAFO) to support a consistent approach to ERA of GM plants, animals and microorganisms. Key aspects of the GRAFO will be presented in this paper.
Abstract:
Organisms may cause harm in a range of different contexts. Multiple regulatory systems and risk analysis frameworks have been developed to address the risks posed by organisms. In many cases, the objective of the analysis is to protect people and/or the environment from biophysical harm. The regulatory risk analysis of genetically modified organisms (GMOs) is one example.
Risk assessment frameworks have been developed and elaborated for many purposes and have adopted a variety of terminologies. The development of guidance and practice of ‘traditional’ Ecological or Environmental Risk Assessment (ERA, eg as articulated by the US Environmental Protection Agency) has its origins in chemical risk assessment and adopted the ‘classical’ Risk = Hazard x Exposure terminology.
However, other risk frameworks adopt Risk = Likelihood x Consequence (including AS/NZS ISO 31000:2009 Risk management). The Office of the Gene Technology Regulator (OGTR) has adopted this terminology for the regulatory risk analysis of genetically modified organisms. OGTR’s experience is that the R = L x C function is more suited to the biological assessment ie the risk assessment of organisms.
The OGTR is developing a Generic Risk Analysis Framework for Organisms (GRAFO) to formalise a consistent terminology and approach for risk assessments of different types of GMOs eg plants, animals, microorganisms. The underlying premise of the GRAFO is that all organisms share common features and that their interactions with the environment can be characterised generically.
This paper will describe a set of common, biologically based risk factors that can be applied to risk assessments of different organisms. Key concepts for the risk factors are: the invasiveness or infectivity; harms; vulnerability; and resilience.
In Australia, the Office of the Gene Technology Regulator (OGTR) regulates GMOs to protect human health and the environment, and the regulation is based on environmental risk assessment (ERA). Although there are different types of GMOs, they are all organisms. OGTR has developed a generic risk analysis framework for organisms (GRAFO) to support a consistent approach to ERA of GM plants, animals and microorganisms. Key aspects of the GRAFO will be presented in this paper.
Abstract:
Organisms may cause harm in a range of different contexts. Multiple regulatory systems and risk analysis frameworks have been developed to address the risks posed by organisms. In many cases, the objective of the analysis is to protect people and/or the environment from biophysical harm. The regulatory risk analysis of genetically modified organisms (GMOs) is one example.
Risk assessment frameworks have been developed and elaborated for many purposes and have adopted a variety of terminologies. The development of guidance and practice of ‘traditional’ Ecological or Environmental Risk Assessment (ERA, eg as articulated by the US Environmental Protection Agency) has its origins in chemical risk assessment and adopted the ‘classical’ Risk = Hazard x Exposure terminology.
However, other risk frameworks adopt Risk = Likelihood x Consequence (including AS/NZS ISO 31000:2009 Risk management). The Office of the Gene Technology Regulator (OGTR) has adopted this terminology for the regulatory risk analysis of genetically modified organisms. OGTR’s experience is that the R = L x C function is more suited to the biological assessment ie the risk assessment of organisms.
The OGTR is developing a Generic Risk Analysis Framework for Organisms (GRAFO) to formalise a consistent terminology and approach for risk assessments of different types of GMOs eg plants, animals, microorganisms. The underlying premise of the GRAFO is that all organisms share common features and that their interactions with the environment can be characterised generically.
This paper will describe a set of common, biologically based risk factors that can be applied to risk assessments of different organisms. Key concepts for the risk factors are: the invasiveness or infectivity; harms; vulnerability; and resilience.
The relationship between risk governance and public engagement in relation to complex environmental issues
So you think you’re an impartial judge? Confirmation bias in conservation decision making under uncertainty
Keywords: Subjective judgement, Confirmation bias, Environmental decision making, Biodiversity conservation, Empirical study
Author: S. Sana Bau
Affiliation: The University of Melbourne
Email address: s.bau@student.unimelb.edu.au
Lay summary:
Confirmation bias is the tendency to seek and interpret information that agrees with one’s initial beliefs. My survey of 306 participants demonstrates that confirmation bias affects how people interpret information that can help make decisions in conservation management.
Abstract:
Subjective judgement is the most common method of dealing with evidence in conservation management, a field that is characterised by high uncertainty. This study explores the influence of confirmation bias, one of several systematic unconscious judgement biases, in the interpretation of evidence informing a conservation decision making task.
The presence and effect of confirmation bias on judgement tasks related to conservation decision making was investigated via an online experiment. Australia’s Great Barrier Reef (GBR) is in the midst of significant, multi-decadal environmental decline. There are multiple causal hypotheses about threatening processes in the GBR, which prompt different, competing management interventions. The experiment consisted of two key components: a before/after comparison of belief in a hypothesis, and a rating task to assess the degree of perceived support in the interpretation of relevant evidence. First, participants selected their preferred management intervention from four options, representing an initial hypothesis about the probable cause of decline, and assigned a measure of confidence in their choice. Then they reviewed a body of evidence consisting of a series of statements that could be used to inform their final decision. These statements were rated according to their perceived support for the initial hypothesis. Three treatment levels for “support” were included in the analysis, which determined the level of agreement of the information presented to participants according to their initial hypothesis: “Low” (more contradictory statements than supportive), “Medium” (equal numbers of contradictory and supportive statements), and “High” (more supportive statements than contradictory).
Results show a clear tendency to preferentially weight confirmatory evidence in interpreting information used to inform a conservation decision. Comparison of preferences before and after exposure to a body of evidence reveals a tendency to maintain consistency with initial hypotheses. These findings strongly suggest that confirmation bias influences subjective judgement in decision making in an environmental context characterised by high risk and uncertainty.
Environmental challenges demand effective, defensible decision making. The impact of unconscious biases on risk judgement is an important, but rarely-acknowledged, barrier to effective decisions. Insights from research on confirmation bias have direct relevance to conservation practice, due to the high uncertainty of complex natural systems intersected with social, economic and political dimensions. The findings of this research address a gap in understanding about subjective judgement in conservation decision making, in particular, relating to the way that individuals engage with evidence and risk-based information in controversial decision contexts. These findings shed light on risk perception in complex environmental problems and may improve risk communication in conservation practice.
Confirmation bias is the tendency to seek and interpret information that agrees with one’s initial beliefs. My survey of 306 participants demonstrates that confirmation bias affects how people interpret information that can help make decisions in conservation management.
Abstract:
Subjective judgement is the most common method of dealing with evidence in conservation management, a field that is characterised by high uncertainty. This study explores the influence of confirmation bias, one of several systematic unconscious judgement biases, in the interpretation of evidence informing a conservation decision making task.
The presence and effect of confirmation bias on judgement tasks related to conservation decision making was investigated via an online experiment. Australia’s Great Barrier Reef (GBR) is in the midst of significant, multi-decadal environmental decline. There are multiple causal hypotheses about threatening processes in the GBR, which prompt different, competing management interventions. The experiment consisted of two key components: a before/after comparison of belief in a hypothesis, and a rating task to assess the degree of perceived support in the interpretation of relevant evidence. First, participants selected their preferred management intervention from four options, representing an initial hypothesis about the probable cause of decline, and assigned a measure of confidence in their choice. Then they reviewed a body of evidence consisting of a series of statements that could be used to inform their final decision. These statements were rated according to their perceived support for the initial hypothesis. Three treatment levels for “support” were included in the analysis, which determined the level of agreement of the information presented to participants according to their initial hypothesis: “Low” (more contradictory statements than supportive), “Medium” (equal numbers of contradictory and supportive statements), and “High” (more supportive statements than contradictory).
Results show a clear tendency to preferentially weight confirmatory evidence in interpreting information used to inform a conservation decision. Comparison of preferences before and after exposure to a body of evidence reveals a tendency to maintain consistency with initial hypotheses. These findings strongly suggest that confirmation bias influences subjective judgement in decision making in an environmental context characterised by high risk and uncertainty.
Environmental challenges demand effective, defensible decision making. The impact of unconscious biases on risk judgement is an important, but rarely-acknowledged, barrier to effective decisions. Insights from research on confirmation bias have direct relevance to conservation practice, due to the high uncertainty of complex natural systems intersected with social, economic and political dimensions. The findings of this research address a gap in understanding about subjective judgement in conservation decision making, in particular, relating to the way that individuals engage with evidence and risk-based information in controversial decision contexts. These findings shed light on risk perception in complex environmental problems and may improve risk communication in conservation practice.
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