Probability functions to build composite indicators: A methodology to measure environmental impacts of genetically modified crops |
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| Institution: | 1. School of Agriculture, Policy and Development, University of Reading, Whiteknights, P.O. Box 237, RG6 6AR Reading, UK;2. Department of Economics, Pablo de Olavide University, Ctra. de Utrera, km. 1, E-41013 Seville, Spain;1. Douglas Stephens Surgical Research Laboratory, Murdoch Children’s Research Institute, Parkville, Victoria, Australia;2. Department of Pediatrics, University of Melbourne, Parkville, Victoria, Australia;3. Urology Department, Royal Children’s Hospital, Parkville, Victoria, Australia;4. Medical School, University of Groningen, Groningen, The Netherlands;1. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy;2. Aquatic Ecology, Faculty of Biology, University of Duisburg-Essen, Universitätsstraße 5, 45141 Essen, Germany;3. Bioforum GmbH, Sudetenstr. 34, DE-73230 Kirchheim/Teck, Germany;4. Centre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UK;5. Centre for Hydrographic Studies, CEDEX, C/ Paseo Bajo de la Virgen del Puerto 3, Madrid 28005, Spain;6. Federal Agency of Water Management, Institute of Freshwater Ecology, Fisheries Management and Lake Research, Scharfling 18, 5310 Mondsee, Austria;7. SYKE, University of Oulu, P.O. Box 413, 90014 Oulu, Finland;8. Bowburn Consultancy, 11 Monteigne Drive, Bowburn, Durham DH6 5QB, UK;9. Norwegian Institute for Water Research, Gaustadalléen 21, Oslo N-0349, Norway;10. Department Environmental Sciences, University of Helsinki, P.O. Box 65, 00014 Helsinki, Finland;11. Systema GmbH, Environment Agency, Bensasteig 8, 1140 Vienna, Austria;12. Environment Agency, Kings Meadow Road, Reading RG1 8DQ, UK;13. Centre for Water Management, Zuiderwagenplein 2, Lelystad, NL-8200 AA, The Netherlands;14. Institute of Inland Fisheries, Im Königswald 2, 14469 Potsdam, Germany;15. Department of Bioscience, Aarhus University, Vejlsøvej 25, P.O. Box 314, DK-8600, Silkeborg, Denmark;p. Norwegian Institute for Nature Research, Gaustadalléen 21, Oslo 0349, Norway;r. Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy;s. DWS Hydro-Ökologie GmbH, Zentagasse 47, Vienna A-105, Austria;1. Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Jiangsu Key Laboratory of Crops Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College of Yangzhou University, Yangzhou, 225009, PR China;2. Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, PR China;3. Agricultural Research Cooperation, Biotechnology and Biosafety Research Center, Khartoum, Sudan;1. University of Pécs - Faculty of Business and Economics, Rákóczi út 80, 7622, Pécs, Hungary;2. Blue Economy Research Centre, Hungary;3. Metropolitan State University of Denver, 890 Auraria Pkwy #310, Denver, CO 80204, USA |
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| Abstract: | There is an on-going debate on the environmental effects of genetically modified crops to which this paper aims to contribute. First, data on environmental impacts of genetically modified (GM) and conventional crops are collected from peer-reviewed journals, and secondly an analysis is conducted in order to examine which crop type is less harmful for the environment. Published data on environmental impacts are measured using an array of indicators, and their analysis requires their normalisation and aggregation. Taking advantage of composite indicators literature, this paper builds composite indicators to measure the impact of GM and conventional crops in three dimensions: (1) non-target key species richness, (2) pesticide use, and (3) aggregated environmental impact. The comparison between the three composite indicators for both crop types allows us to establish not only a ranking to elucidate which crop is more convenient for the environment but the probability that one crop type outperforms the other from an environmental perspective. Results show that GM crops tend to cause lower environmental impacts than conventional crops for the analysed indicators. |
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| Keywords: | Composite indicators GM crops Conventional crops Environmental impacts Meta-analysis Probability |
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