AN INDIVIDUAL-BASED MODELING APPROACH FOR EVALUATION OF ENDPOINT SENSITIVITY IN HARPACTICOID COPEPOD LIFE-CYCLE TESTS AND OPTIMIZATION OF TEST DESIGN

Authored by Thomas G Preuss, Markus Brinkmann, Magnus Breitholtz, Elin Lundstroem, Bengt-Erik Bengtsson

Date Published: 2011

DOI: 10.1002/etc.614

Sponsors: European Union

Platforms: Delphi

Model Documentation: ODD Flow charts

Model Code URLs: Model code not found

Abstract

In the present study, an individual-based model for Nitocra spinipes was developed and used to optimize the test design of a proposed Organisation for Economic Co-operation and Development test guideline for harpacticoid copepods. The variability between individuals was taken into account, based on measured data, leading to stochastic model output. Virtual experiments were performed with the model to analyze the endpoint sensitivity and the effect of number of replicates and inspection intervals on statistical power. The impact of mortality was evaluated; most sublethal effects could not be determined if the mortality was >= 70\%. Most sensitive to mortality was the determination of effects on brood size, for which the statistical power was reduced at 10\% mortality. Our simulations show that increasing the number of replicates from 72 to 96 or 144 has little impact on the statistical power, whereas 25 replicates disallow relevant endpoint detection. Furthermore, it was demonstrated that the proposed ID inspection interval can be shifted to a 3D interval, without losing statistical power. It was demonstrated that developmental endpoints have a higher statistical power than reproductive endpoints in the current test design. The present study highlights the usefulness of individual-based models for optimizing the experimental design. The use of such models in the development of standard test guidelines will lead to a faster and less resource-demanding process. Environ. Toxicol. Chem. 2011:30:2353-2362. (C) 2011 SETAC

Tags

Mechanistic effect models Population-dynamics Chemicals Daphnia-magna Reproduction Ecological risk-assessment