Seasonal variability in metal and metalloid burdens of mussels: using data from the German Environmental Specimen Bank to evaluate implications for long-term mussel monitoring programs 机翻标题: 暂无翻译,请尝试点击翻译按钮。

2020-02-10

Background: Metal and metalloid concentrations in mussels can vary between seasons. In biota monitoring, the sampling time is therefore an important issue. Within the German Environmental Specimen Bank (ESB) program blue mussels (Mytilus edulis Complex) are sampled regularly since the 1980s. The samples are collected in two-monthly intervals at two North Sea sites and in 6-month intervals at one Baltic Sea site. All samples from one site and year are combined to annual composite samples and archived as sub-samples under cryogenic conditions. In order to investigate a possible reduction of the number of annual sampling intervals while maintaining comparability with the long-term composite sample data, the seasonal variability of metals/metalloids was analyzed based on the half-yearly and bimonthly samples of 2013, 2015 and 2017. Results: In mussels from the North Sea site Eckwarderhoerne seasonality of metals/metalloids was comparable in all 3 years (arsenic being the only exception). At the North Sea site Koenigshafen seasonality of cobalt, nickel, cadmium, copper, lead, and arsenic was comparable in 2013 and 2015 but not in 2017, while selenium showed the same seasonality in all 3 years. Within 1 year, concentrations of metals and metalloids can vary by the same order of magnitude as observed between annual composite samples of different years making it impossible to select just one representative sampling time point per year that would provide the same information as the respective annual composite sample. Conclusions: The findings highlight the importance of carefully selecting the sampling time point when using mussels in biota monitoring. For the German ESB program it is recommended to continue with the current sampling strategy and analyze annual composite samples in order to maintain comparability with the long-term data series, which are a special feature of the ESB.

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