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Scientific Opinion on the use of existing environmental surveillance networks to support the post-market environmental monitoring of genetically modified plants


Arpaia, Salvatore; Birch, Andrew Nicholas Edmund; Chesson, Andrew; du Jardin, Patrick; Gathmann, Achim; Gropp, Jürgen; Lieve, Herman; Hoen-Sorteberg, Hilde-Gunn; Jones, Huw; Kiss, József; Kleter, Gijs; Løvik, Martinus; Messéan, Antoine; Naegeli, Hanspeter; Nielsen, Kaare Magne; Ovesná, Jaroslava; Perry, Joe; Rostoks, Nils (2014). Scientific Opinion on the use of existing environmental surveillance networks to support the post-market environmental monitoring of genetically modified plants. EFSA Journal, 12(11):3883.

Abstract

Following a request from the European Commission, a set of assessment criteria was developed to support the selection of existing environmental surveillance networks for post-market environmental monitoring (PMEM) of genetically modified plants (GMPs). In compliance with these criteria, some networks and associated programmes were identified as being of potential use subject to further case-by-case analysis. When considering PMEM of GMPs, the approach would also require comparing sites monitored by the networks and the locations where GMPs are cultivated. The reporting of the sites surveyed by networks and locations of cultivated GMPs should thus follow the same standards in order to ensure interoperability and to potentially establish a causal link between a change observed and the GMPs. In this respect, technical support might be required by networks to transform their data records into workable standards. Moreover, the EFSA GMO Panel was asked by the European Commission to examine the sensitivity of statistical analyses used by the networks to detect change. A decision tree is provided for selecting the optimal method for statistical analysis based on the study design and the datasets from networks. Sufficient statistical power needs to be ensured to detect an effect for a particular indicator. Sample size is one of the main contributing factors in determining the power of any network to detect an effect of a product release into the environment. Increasing the sample size implies variable extra-costs depending on whether data are collected by volunteers or professionals. A more powerful statistical analysis can also be achieved by pooling datasets collected by different networks; this needs further investigation because of important covariates leading to differentiated responses. In general, PMEM would benefit from a move towards ‘open data’ policies for re-analysis or pooling data collected by different networks.

Following a request from the European Commission, a set of assessment criteria was developed to support the selection of existing environmental surveillance networks for post-market environmental monitoring (PMEM) of genetically modified plants (GMPs). In compliance with these criteria, some networks and associated programmes were identified as being of potential use subject to further case-by-case analysis. When considering PMEM of GMPs, the approach would also require comparing sites monitored by the networks and the locations where GMPs are cultivated. The reporting of the sites surveyed by networks and locations of cultivated GMPs should thus follow the same standards in order to ensure interoperability and to potentially establish a causal link between a change observed and the GMPs. In this respect, technical support might be required by networks to transform their data records into workable standards. Moreover, the EFSA GMO Panel was asked by the European Commission to examine the sensitivity of statistical analyses used by the networks to detect change. A decision tree is provided for selecting the optimal method for statistical analysis based on the study design and the datasets from networks. Sufficient statistical power needs to be ensured to detect an effect for a particular indicator. Sample size is one of the main contributing factors in determining the power of any network to detect an effect of a product release into the environment. Increasing the sample size implies variable extra-costs depending on whether data are collected by volunteers or professionals. A more powerful statistical analysis can also be achieved by pooling datasets collected by different networks; this needs further investigation because of important covariates leading to differentiated responses. In general, PMEM would benefit from a move towards ‘open data’ policies for re-analysis or pooling data collected by different networks.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:05 Vetsuisse Faculty > Institute of Veterinary Pharmacology and Toxicology
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:18 November 2014
Deposited On:19 Feb 2015 14:21
Last Modified:05 Apr 2016 18:54
Publisher:European Food Safety Authority (EFSA), Parma
ISSN:1831-4732
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.2903/j.efsa.2014.3883
Official URL:http://www.efsa.europa.eu/en/efsajournal/pub/3883.htm
Permanent URL: https://doi.org/10.5167/uzh-106284

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