Willem Talloen | PubMed Health

PubMed2006

Microcontaminant accumulation, physiological condition and bilateral asymmetry in zebra mussels (Dreissena polymorpha) from clean and contaminated surface waters.

Chemical and biological monitoring of pollution in the aquatic environment is essential to assess the quality of surface waters. Zebra mussels (Dreissena polymorpha) have been used extensively to monitor pollution in freshwater environments, especially in bioaccumulation studies, whereby pollutant levels in tissues have been used as a measure of exposure. However, there is a need for good biomarkers that reflect the impact of exposure to pollutants. Bilateral asymmetry, commonly used as a measure of developmental instability, has a high potential as a biomarker to monitor stress caused by pollution. Nevertheless, until recently, no studies have evaluated bilateral asymmetry as a biomarker in zebra mussels. Biomarkers related to the energy metabolism may give a good indication of the physiological cost of exposure to pollution. In this study, we investigated whether the physiological condition (energy reserves and condition indices) and bilateral asymmetry of shells of zebra mussels are potentially useful biomarkers to monitor the impact of micropollution, such as trace metals, polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and di(p-chlorophenyl) dichloroethylene (p,p'-DDE) in the freshwater environment. Bilateral asymmetry of the zebra mussel shells was examined with respect to levels of pollutants accumulated in the mussels and compared to the physiological condition of the mussels. Levels of PCBs and several trace metals (especially Cd, Cu and Zn) were very high in four of the six sampling locations and in some locations the physiological condition of the mussels was significantly depressed. Nevertheless we did not find any relation (on individual or population level) with bilateral asymmetry of zebra mussel shells. Therefore our results suggest that bilateral asymmetry of zebra mussel shells is not a good measure for the impact of pollution in freshwater ecosystems. The energy reserves and condition indices, on the other hand, gave a valuable indication of the physiological condition of zebra mussels and are useful to monitor the impact of pollution if physiological and environmental factors are taken into account.

Animals↗

PubMed2005

High variation in developmental instability under non-normal developmental error: a Bayesian perspective.

The developmental mechanisms behind developmental instability (DI) are only poorly understood. Nevertheless, fluctuating asymmetry (FA) is often used a surrogate for DI. Based on statistical arguments it is often assumed that individual levels of FA are only weakly associated with the underlying DI. Patterns in FA therefore need to be interpreted with caution, and should ideally be transformed into patterns in DI. In order to be able to achieve that, assumptions about the distribution of developmental errors must be made. Current models assume that errors during development are additive and independent such that they yield a normal distribution. The observation that the distribution of FA is often leptokurtic has been interpreted as evidence for between-individual variation in DI. This approach has led to unrealistically high estimates of between-individual variation in DI, and potentially incorrect interpretations of patterns in FA, especially at the individual level. Recently, it has been suggested that the high estimates of variation in DI may be biased upward because either developmental errors are log-normal or gamma distributed and/or low measurement resolution of FA. A proper estimation of the amount (and shape) of heterogeneity in DI is crucial for the interpretation of patterns in FA and their transformation into patterns in DI. Yet, incorrect model assumptions may render misleading inferences. We therefore develop a statistical model to evaluate the sensitivity of results under the normal error model against the two alternative distributions as well as to investigate the importance of low measurement resolution. An analysis of simulated and empirical data sets indicated that bias due to misspecification of the developmental error distribution can be substantial, yet, did not appear to reduce estimates of variation in DI in empirical data sets to a large extent. Effects of low measurement resolution were neglectable. The importance of these results are discussed in the context of the interpretation of patterns in FA.

Animals↗