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To Editor, We read with great interest the paper entitled ‘‘Traits and stress: keys to identify community effects of low levels of toxicants in test systems’’ by Matthias Liess and Mikhail Beketov (Liess and Beketov 2011). The paper presents a new way to analyse data from microcosms and mesocosms, which the authors claim that to be more sensitive than the commonly-used principal response curves (PRC) method (Van den Brink and Ter Braak 1999). Since PRC was developed more than a decade ago, new developments in the field of analysing community responses to stress are very welcome. However, after reading the paper, we have concluded that their new method, i.e. SPEARmesocosm, may not offer the level of improvement suggested and in this letter to the editor we will briefly explain why. Both PRC and SPEARmesocosm display the time-dependent treatment effects of a toxicant. The fundamental difference between the PRC and SPEARmesocosm methods is that PRC is a multivariate statistical method and SPEARmesocosm is a univariate method. For SPEARmesocosm to work, a single index must be constructed on the basis of predictions derived from a priori knowledge of intrinsic sensitivity and life-cycle characteristics (voltinism). By contrast, PRC does not need this a priori knowledge and can work with multiple indices. In microcosm and mesocosm studies for which it was developed it is usually applied on the original taxon composition data. PRC is thus a purely statistical method for analysing empirical data derived from mesocosm and other community-level experiments. PRC partitions the observed variance in the data in time, treatment (which includes interaction with time) and residual variance (which corresponds to the differences between replicates) and summarises the variance explained by treatment and time by showing the timedependent treatment effects in sequential (first, second, etc.) PRC diagrams. These PRC diagrams show the contrasting responses of different (groups of) taxa, very much like the contrasting response of the sensitive univoltine species and the other taxon groups as displayed in Fig. 2 of Liess and Beketov (2011). The agreement of Fig. 2 with PRC would have been even greater if the percentage change would have been plotted on a logarithmic scale. When comparing the statistical methods for analysing the data from such experiments, it is clearly critical that the same endpoints are being compared (using the same input data), otherwise the differences seen in outcomes cannot be reliably attributed to the statistical methods. We feel that the comparison made in Fig. 3 is inappropriate, the comparison is one of apples with oranges. While the PRC diagram shows the dominant response present in the whole invertebrate community, SPEARmesocosm only takes (presumed) sensitive species into account. For a proper comparison, Liess and Beketov could have performed a PRC analysis only using the sensitive univoltine taxa, which would almost certainly have yielded a diagram comparable to Fig. 3b. Probably the sub-dominant responses of the sensitive univoltine taxa would be presented by the second PRC of the P. J. Van den Brink (&) Alterra, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands e-mail: paul.vandenbrink@wur.nl

Response to “traits and stress: keys to identify community effects of low levels of toxicants in test systems” by Liess and Beketov (2011)