Quote this article:D. A. Andow,Gabor L. L?vei,Salvatore Arpaia,Lewis Wilson,Eliana M. G. Fontes,Angelika Hilbeck,Andreas Lang,Nguy?n V?n Tu?t,C. S. S. Pires,E. R. Sujii,Claudia Zwahlen,A. N. E. Birch,Deise M. F. Capalbo,Kristina Prescott,Celso Omoto,Adam R. Zeilinger. An ecologically-based method for selecting ecological indicators for assessing risks to biological diversity from genetically-engineered plants[J]. Journal of Biosafety, 2013, 22(3): 141-156.
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An ecologically-based method for selecting ecological indicators for assessing risks to biological diversity from genetically-engineered plants
D. A. Andow1, Gabor L. L?vei2, Salvatore Arpaia3, Lewis Wilson4, Eliana M. G. Fontes5, Angelika Hilbeck6, Andreas Lang7, Nguy?n V?n Tu?t8, C. S. S. Pires9, E. R. Sujii9, Claudia Zwahlen1, A. N. E. Birch10, Deise M. F. Capalbo11, Kristina Prescott1, Celso Omoto12, Adam R. Zeilinger1
Author NameAffiliation
D. A. Andow Department of Entomology, University of Minnesota, St. Paul, MN 55108 USA 
Gabor L. L?vei Aarhus University, Department of Agroecology, Flakkebjerg Research Centre, Fors?gsvej 1, DK-4200 Slagelse Denmark 
Salvatore Arpaia ENEA–Research Centre Trisaia, S.S. 106 Jonica Km 419,5, I-75026 Rotondella (MT), Italy 
Lewis Wilson CSIRO Cotton Research Unit - Myall Vale, Wee Waa Road, Myall Vale NSW 2390 Australia 
Eliana M. G. Fontes Embrapa Genetic Resources and Biotechnology, Biological Control Area, Parque Esta??o Biológica - PqEB Final W5 norte, 70770-900, Brasilia, DF 
Angelika Hilbeck Swiss Federal Institute of Technology Institute of Integrative Biology, Universit?tstrasse 16, CH-8092 Zurich, Switzerland 
Andreas Lang Institute of Environmental Geosciences, University of Basel, Basel, Switzerland 
Nguy?n V?n Tu?t Food Crops Research Institute, MARD, Hai Duong, Vietnam 
C. S. S. Pires Embrapa Genetic Resources and Biotechnology Laboratory of Ecology and Biosafety, Parque Esta??o Biológica - PqEB Final W5 norte, 70770-900, Brasilia, DF 
E. R. Sujii Embrapa Genetic Resources and Biotechnology Laboratory of Ecology and Biosafety, Parque Esta??o Biológica - PqEB Final W5 norte, 70770-900, Brasilia, DF 
Claudia Zwahlen Department of Entomology, University of Minnesota, St. Paul, MN 55108 USA 
A. N. E. Birch Ecological Science Group, James Hutton Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK 
Deise M. F. Capalbo Embrapa Environment Rodovia SP 340, PO Box 69 Km 127.5, Jaguariúna, SP, Brazil 13820-000 
Kristina Prescott Department of Entomology, University of Minnesota, St. Paul, MN 55108 USA 
Celso Omoto Universidade de S?o Paulo – ESALQ Department of Entomology and Acarology, Av. Pádua Dias, 11, 13418-900 Piracicaba, SP, Brasil 
Adam R. Zeilinger Department of Entomology, University of Minnesota, St. Paul, MN 55108 USA 
Abstract:
The environmental risks associated with genetically-engineered (GE) organisms have been controversial, and so have the models for the assessment of these risks. We propose an ecologically-based environmental risk assessment (ERA) model that follows the 1998 USEPA guidelines, focusing on potential adverse effects to biological diversity. The approach starts by (1) identifying the local environmental values so the ERA addresses specific concerns associated with local biological diversity. The model simplifies the indicator endpoint selection problem by (2) classifying biological diversity into ecological functional groups and selecting those that deliver the identified environmental values. (3) All of the species or ecosystem processes related to the selected functional groups are identified and (4) multi-criteria decision analysis (MCDA) is used to rank the indicator endpoint entities, which may be species or ecological processes. MCDA focuses on those species and processes that are critical for the identified ecological functions and are likely to be highly exposed to the GE organism. The highest ranked indicator entities are selected for the next step. (5) Relevant risk hypotheses are identified. Knowledge about the specific transgene and its possible environmental effects in other countries can be used to assist development of risk hypotheses. (6) The risk hypotheses are ranked using MCDA with criteria related to the severity of the potential risk. The model emphasizes transparent, expert-driven, ecologically-based decision-making and provides formal methods for completing a screening level-ERA that can focus ERA on the most significant concerns. The process requires substantial human input but the human capital is available in most countries and regions of the world.
Key words:  genetically engineered organisms  environmental risk assessment  ecosystem services
AttacheList
1.Department of Entomology, University of Minnesota, St. Paul, MN 55108 USA;2.Aarhus University, Department of Agroecology, Flakkebjerg Research Centre, Fors?gsvej 1, DK-4200 Slagelse Denmark;3.ENEA–Research Centre Trisaia, S.S. 106 Jonica Km 419,5, I-75026 Rotondella (MT), Italy;4.CSIRO Cotton Research Unit - Myall Vale, Wee Waa Road, Myall Vale NSW 2390 Australia;5.Embrapa Genetic Resources and Biotechnology, Biological Control Area, Parque Esta??o Biológica - PqEB Final W5 norte, 70770-900, Brasilia, DF;6.Swiss Federal Institute of Technology, Institute of Integrative Biology, Universit?tstrasse 16, CH-8092 Zurich, Switzerland;7.Institute of Environmental Geosciences, University of Basel, Basel, Switzerland;8.Food Crops Research Institute, MARD, Hai Duong, Vietnam;9.Embrapa Genetic Resources and Biotechnology, Laboratory of Ecology and Biosafety, Parque Esta??o Biológica - PqEB Final W5 norte, 70770-900, Brasilia, DF;10.Ecological Science Group, James Hutton Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK;11.Embrapa Environment, Rodovia SP 340, PO Box 69 Km 127.5, Jaguariúna, SP, Brazil 13820-000;12.Universidade de S?o Paulo – ESALQ, Department of Entomology and Acarology, Av. Pádua Dias, 11, 13418-900 Piracicaba, SP, Brasil