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The minimum detectable difference (MDD) and the interpretation of treatment-related effects of pesticides in experimental ecosystems

In the European registration procedure for pesticides, microcosm and mesocosm studies are the highest aquatic experimental tier to assess their environmental effects. Evaluations of microcosm/mesocosm studies rely heavily on no observed effect concentrations (NOECs) calculated for different populati...

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Detalles Bibliográficos
Autores principales: Brock, T. C. M., Hammers-Wirtz, M., Hommen, U., Preuss, T. G., Ratte, H-T., Roessink, I., Strauss, T., Van den Brink, P. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544645/
https://www.ncbi.nlm.nih.gov/pubmed/25119278
http://dx.doi.org/10.1007/s11356-014-3398-2
Descripción
Sumario:In the European registration procedure for pesticides, microcosm and mesocosm studies are the highest aquatic experimental tier to assess their environmental effects. Evaluations of microcosm/mesocosm studies rely heavily on no observed effect concentrations (NOECs) calculated for different population-level endpoints. Ideally, a power analysis should be reported for the concentration–response relationships underlying these NOECs, as well as for measurement endpoints for which significant effects cannot be demonstrated. An indication of this statistical power can be provided a posteriori by calculated minimum detectable differences (MDDs). The MDD defines the difference between the means of a treatment and the control that must exist to detect a statistically significant effect. The aim of this paper is to expand on the Aquatic Guidance Document recently published by the European Food Safety Authority (EFSA) and to propose a procedure to report and evaluate NOECs and related MDDs in a harmonised way. In addition, decision schemes are provided on how MDDs can be used to assess the reliability of microcosm/mesocosm studies and for the derivation of effect classes used to derive regulatory acceptable concentrations. Furthermore, examples are presented to show how MDDs can be reduced by optimising experimental design and sampling techniques. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11356-014-3398-2) contains supplementary material, which is available to authorized users.