Skip to main content

Advertisement

Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

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

Abstract

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.

Background

Blue mussels are frequent inhabitants of boreal and temperate coastal waters [1, 2]. They play an important role as primary consumers in the coastal food webs by filtrating algae and bacteria from the surrounding water while being an important food source for other species, like polychaetes, sea stars, sea birds and otters. Moreover, blue mussels are coveted food and thus represent a link between the marine environment and human health [3]. These features in concert with their widespread abundance, their sedentary way of life, and their relatively high tolerance towards environmental conditions make them ideal sentinels for environmental pollution and indicators for marine and coastal biodiversity (e.g., for ICES [4], OSPAR [5], HELCOM [6, 7], the Arctic Monitoring and Assessment Program AMAP [8, 9], and the Mussel Watch Programs [10, 11]).

Most monitoring programs rely on yearly samples that are collected outside the spawning season. It is well known, however, that chemicals’ concentrations in bivalves may vary during the year due to fluctuations in environmental conditions such as temperature, turbidity, salinity, riverine inputs, primary production and the presence of contaminants, and due to biotic factors like mussel size, age, soft tissue weight, filtration rate, sex, and the gametogenetic stage (e.g., [1, 10, 12,13,14,15,16,17,18,19]).

Metal burdens of mussels are often highest in winter (e.g., [13, 20]). This is the time of year when the nutritional status of the mussels is likely to be suboptimal and weight-related metal concentrations may increase despite constant body burdens [21]. Levels of lipophilic substances, in contrast, may be highest when lipid-rich gametes are formed (e.g., [22, 23]: for blue mussels from the North and Baltic Seas this would be in spring and early summer). Contamination with other compounds like pharmaceuticals, personal care products [24] or tributyltin (TBT) [14, 25, 26] seems to be triggered by season-dependent emissions, e.g., winter outbreaks of influenza in the case of pharmaceuticals or dry-dock works in winter in the case of TBT [27].

To compensate for such variations, normalization of chemicals’ concentrations in tissues is discussed. Phillips [21] observed a significant correlation between cadmium levels and wet weight of M. edulis. Normalizing the data to a common wet weight strongly reduced seasonal variability. No such relationships were detected for zinc (Zn), lead (Pb) and copper (Cu). Others based data normalization on the mussel’s condition index [28,29,30]. The EU Guidance Document No. 32 [31] recommends normalizing priority substances concentrations in mussels to a default dry weight content of 8.3% (e.g., for metals) or a default lipid content of 1% (for lipophilic compounds).

The German ESB pursues a different strategy to deal with possible seasonal variations: since the mid-1980s, blue mussels are sampled every second month at two locations in the North Sea and twice per year at one site in the Baltic Sea (www.umweltprobenbank.de/en). All samples of one sampling area from 1 year are combined to an annual composite sample that should reflect the mean annual mussel burdens. Since 2013, also a subset of the original 2- or 6-monthly samples is stored in parallel, to allow for the investigation of seasonal trends. The frequent sampling, however, is relatively cost and labor intensive.

To evaluate a possible reduction of the number of samplings per year, a study was initiated with the aim to investigate whether certain time points throughout the year can capture the average annual levels of chemicals of mussels at the respective sampling locations. This would allow perpetuating the already existing long time series for ESB mussels with less effort. The original in 2- or 6-monthly intervals sampled mussels from 3 years (2013, 2015, 2017) were analyzed for arsenic, selenium, TBT, methylmercury and a set of metals cobalt (Co), nickel (Ni), Cu, cadmium (Cd), Pb and mercury (Hg). Bioaccumulation can further depend on the chemical species of an element as methylmercury in case of mercury or different compounds like arsenobetaine and arsenosugars in case of arsenic. Due to the fact that long-term data were only available for arsenic—but not for arsenic species, the seasonal samples were also investigated for arsenic only. The results were compared to the data of the respective annual composite samples. Possible correlations between substance concentrations and biometric parameters were analyzed to identify parameters that account for seasonal variability and could be used for data normalization. Finally, seasonal variations were compared with long-term trends based on the respective annual composite samples.

Material and methods

Sampling

Blue mussels are sampled every second month at two North Sea sites and twice per year (June and November/December) at one site in the Baltic Sea (Fig. 1) following an ESB standard operating procedure (SOP; [32]). The North Sea sites are located in the Lower Saxony Wadden Sea (site Eckwarderhoerne) and the Schleswig–Holstein Wadden Sea (site Koenigshafen). The Baltic Sea site is located in the Bodden National Park of Western Pomerania (site Darsser Ort). Per sampling, at least 100 individuals are collected. A suitable criterion for reducing the natural variability is the shell length of the mussels. For practical reasons, relatively large shells are sought and for biological reasons, adult mussels older than 2 years should be sampled [32]. The length class corresponding to the respective body of water was determined for each sampling site by a screening. For longer-term samples series, the size distribution is reviewed over several years and the size class to be collected is readjusted if necessary. A representative subsample of 50 mussels is biometrically characterized (i.e., recording of shell length and wet weight, and soft body wet weight with and without breathing water). A further subset of at least 50 mussels is used for homogenization and chemical analysis.

Fig. 1
figure1

Blue mussel sampling sites of the German Environmental Specimen bank

Mussels are deep-frozen at < − 130 °C directly after sampling and are processed for chemical analyses and storage without interrupting the cold chain following the ESB SOPs. First, the shells are removed under a clean bench after a short thawing period. Then, the frozen mussel soft bodies are cryo-milled [33].

All monthly samples of 1 year and sampling site are finally combined to form one annual composite sample per site. Since 2013, a limited number of the original monthly samples are stored in parallel to allow for seasonal investigations. Routinely chemical analysis is performed on the annual samples. In the present study, additional chemical analysis was performed on the monthly samples from the selected years.

This procedure (i.e., cryomilling of frozen softbodies) implies that the respiratory water of the mussels is included in the samples. Thus, the concentrations of substances of German ESB samples are diluted by a factor of about 1.3 to 2.1, compared to mussels dissected in fresh condition in other studies [32]. As described before, a subset of 50 mussels per sampling is biometrically characterized, and for this subset data of respiratory water is available. For each mussel the dilution factor was calculated by using the wet weight with respiratory water and without and the mean for each year was calculated. This is relevant for any comparison of contaminant concentrations with reference values or when results of the ESB are compared to data of other programs. Since 2013, the amount of respiratory water in the ESB samples is systematically recorded in the mussel subset used for biometrical characterization. Thus, for all data since 2013, it is possible to exclude the respiratory water fraction when calculating wet weight-based contaminant concentrations, while for earlier years one would have to resort to default values. To avoid bias by heterogenous data sets, in the present study the dilution effect by respiratory water was neglected when long-term data of annual composite samples were compared and when analyzing correlations between biometrical parameters and substance concentrations. By contrast, when comparing recent monthly and annual data with reference values either dry weight-based concentrations were used or wet weight-based concentrations calculated without respiratory water. Respiratory water correction was performed by using the mean dilution factor of the respective year by dividing the concentrations of the measured elements with the mean dilution factor.

Digestion

Homogenates of samples were lyophilized (Alpha 1-2LDplus, Christ, Osterode, Germany) and then digested by a microwave procedure (heating to 220 °C and holding the temperature for 30 min). For digestion, around 200 mg of sample material was transferred to quartz vials and digested with concentrated nitric acid (Rotipuran supra 69%, Roth, Karlsruhe, Germany) in an Ultra Clave microwave-heated digester (MLS GmbH, Leutkirch, Germany). In each digestion step certified reference material (NIST 2976, Mussel Tissue; NIST 1566b Oyster tissue), internal reference material (mussel samples of the ESB) as well as analytical blank samples were digested along with the samples to verify the completeness of the digestion procedure. The procedure is highly standardized following an ESB SOP [34]. This digestion procedure was used for metals and metalloids.

Metal and metalloid analysis

Determination of all metals and metalloids, except mercury, was performed with an Agilent ICP-MS 7500ce (Agilent Technologies, Waldbronn, Germany) and sample introduction was performed using an autosampler (CETAC 500, Teledyne, Manchester, UK) and the Integrated Sample Introduction System (ISIS; Agilent Technologies, Waldbronn, Germany). The measurement parameters are given in Additional file 1: Table S1. Certified reference materials (Environmental Canada), quality control samples and recalibration standards were measured along with the samples to verify the measurement series. The procedure followed an ESB SOP [35].

Mercury analysis

Measurement of total mercury (here designated as Hg) was performed with dedicated atomic absorption spectrometry (AAS) methods applying a Direct Mercury Analyzer (DMA) instrument (DMA-80 for solid; MLS GmbH, Leutkirch, Germany). For details of sample treatment and measurement method, see [36].

The analysis of methylmercury (monomethyl mercury cation; MeHg) was performed with SID-GC/ICP-MS (stable isotope dilution-gas chromatography coupled to inductively coupled plasma-mass spectrometry). Pooled muscle tissue (200 mg) samples were extracted by a microwave-assisted procedure with tetramethylammonium hydroxide (TMAH) and the addition of a previously calculated amount of 201Hg-enriched MeHg. After extraction, samples were derivatized with sodium tetrapropylborate. Volatile mercury species were extracted in n-hexane and analyzed by SID-GC/ICP-MS. Data are reported as methyl mercury cation (for details see [36,37,38]). The respective LOQs were in the range of 0.02–0.81 µg kg−1 (derived from blanks measured along with each set of samples).

Organotin analysis

Analysis of organotin compounds (TBT, DBT and MBT cations) was also performed with SID-GC/ICP-MS. The preparation of all samples was performed according to a slightly modified method for isotope dilution analysis (IDA) developed by Point et al. [39]. 200 mg sample material were weighed in a quartz vial to which 3 mL TMAH and a previously calculated amount of 119Sn-enriched butyltin mix (solution in acetic acid/methanol 3:1, ISC Science) of TBT (c = 1.082 µg g−1 as Sn), DBT (c = 0.693 µg g−1 as Sn) and MBT (c = 0.105 µg g−1 as Sn) as internal standard (spike solution) were added. The mixture was equilibrated for at least 30 s. For extraction, the samples were heated up to 60 °C within 10 min and the temperature was held for 5 min. Subsequently, the digestion solutions were sonicated for 15 min. The pH of the digested samples was adjusted to 4.2 ± 0.2 with 0.55 mL HNO3 (69%, suprapur, Roth) and 5.45 mL NaOAc/AcOH-buffer solution (pH 4.66, Merck). As ethylation reagent a 10% solution of sodium tetraethylborate (purity > 98%, ABCR) was prepared and 200 µL of this solution was applied. After equilibrating for 30 s, butyltin compounds were extracted with 2 mL n-hexane (purity ≥ 95%, ChemSolute) by shaking for 1 h and separating the organic layer via centrifugation (15 min, 3500 rpm). For clean-up 3 g anhydrous Na2SO4 (Merck) were filled on top of a silica cartridge (Phenomenex Strata SI-1 Silica, 1000 mg/6 mL) and conditioned with 5 mL n-hexane. Then, butyltin compounds were extracted with 2 × 2 mL n-hexane/acetone (95:5 vol%, both ChemSolute), concentrated to 150 µL and transferred into GC vials. Data reported as organotin cations. GC parameters, GC temperature program and ICP-MS parameters are listed in Additional file1: Table S2.

Substance concentrations are reported on a wet weight (ww) basis if not stated otherwise.

Data treatment

Statistical analysis was performed using MS-Excel or MS-Excel Add-Ins or freely available Internet applications (e.g., VassarStats—Website for Statistical Computation, http://vassarstats.net, or StatTools, http://www.obg.cuhk.edu.hk). The Condition Index (CI) was calculated as follows: (soft body wet weight [g]/shell wet weight [g]) × 100 [3, 40]. Pearson’s correlation coefficient was used to evaluate relationships between biometrical characteristics and chemicals’ concentrations. In case of significance the non-directional probability value p is given. Temporal trends were analyzed using an MS-Excel-based tool (LOESS Trend (Version 1.1) developed by J. Wellmitz, German Environment Agency). The tool fits a locally weighted scatterplot smoother (LOESS; fixed window width of 7 years) through the annual concentration data followed by tests for significance of linear and non-linear trend components by means of an analysis of variance (ANOVA) [41].

Results and discussion

Biometric data

Annual composite samples

During the sampling period 2000–2017, mussels from the sampling site Eckwarderhoerne (Lower Saxony Wadden Sea) were relatively homogenous with respect to biometric parameters. Mean shell length and weight were around 47.0 ± 1.13 mm and 8.13 ± 0.5 g wet weight (ww), respectively. Soft body weights were around 2.55 ± 0.3 g ww (calculated dry weights (dw): 0.20 ± 0.04 g) and water contents were in the range of 90.3–93.7% (including respiratory water).

Mussels from the Schleswig–Holstein Wadden Sea (sampling site Koenigshafen) decreased slightly in size since 2000. Between 2000 and 2017, mean shell length and weight were 57.2 ± 2.7 mm and 13.3 ± 1.89 g. Soft body weight ranged around 4.78 ± 0.87 g ww and 0.36 ± 0.08 g dw with water contents in the range of 90.3–94.3%.

At the Baltic Sea sampling site Darsser Ort, mussels increased in size from 2013 onward. In 2017, mussels were especially large with a mean length of 66.7 mm length. In the period 2000–2017, shell length and weight were in the range of 36.4 ± 9.78 mm and 1.56 ± 1.84 g. Soft body weights were around 1.28 ± 1.45 g ww (calculated dw: 0.070 ± 0.080 g) and water contents ranged between 91.0 and 96.8%.

Monthly samples

The biometrical characteristics of the monthly samples of 2013, 2015 and 2017 are summarized in Additional file 1: Figure S1 and compared to the annual data of the respective years. Figure 2 shows the temporal comparison of the CI of the mussels from all three sites.

Fig. 2
figure2

Condition Index (mean of 50 individuals) of blue mussels (Mytilus edulis Complex) sampled by the German Environmental Specimen Bank at the North Sea sites Eckwarderhoerne (Lower Saxony Wadden Sea) and Koenigshafen (Schleswig–Holstein Wadden Sea) and at the Baltic Sea site Darsser Ort. Shown are the data of monthly samples (red columns) and of the respective annual composite sample (dark columns)

Condition indices of mussels from Eckwarderhoerne were slightly lower compared to Koenigshafen and both were considerably lower than the CIs of mussels from the Baltic Sea site Darsser Ort. The high CIs at Darsser Ort result mainly from significantly lower shell weights at this site (Additional file 1: Figure S1). These differences can in part be attributed to the different living conditions of North Sea and Baltic Sea mussels (e.g., lower salinity of Baltic Sea water).

At all three sites the CIs varied in the course of the year. However, no consistent annual fluctuation was apparent at any site nor was there one consistent month that compares best to the annual composite sample.

As discussed by Beyer and Green [3] the CI depends on the nutritional and reproductive status of the mussel and may vary quite strongly in the course of the year. Thin shells and high soft body weights are typically associated with rapid growth. In temperate waters body weights of mussels decrease to a minimum in spring–summer when spawning occurs. Thereafter weights rapidly increase thanks to good food supply allowing the mussels to build up reserves for the winter season and for gonad development. Depending on the nutritional status, a second spawning may take place in autumn. In the present study, no such common pattern was observed at any site indicating that also other factors played a pivotal role.

Correlation of biometric parameters with levels of chemicals

The influence of shell length and CI on the metal and metalloid burdens of mussels was studied to assess whether one of these biometrical parameters could be used to normalize the data. The results of the correlation analyses are summarized in Additional file 1: Tables S3–S5. No consistent correlations between the CI or the length of mussels and the metal/metalloid concentrations were detected. Correlations differed between sites, between wet weight- and dry weight-based metal/metalloid concentrations and between annual and monthly samples.

The results suggest that the nutritional status of the mussels (expressed as condition index) and the size of the mussels (expressed as shell length) seem to be correlated with the mussels’ metal/metalloid concentrations, but the observed differences between the sampling sites and between the annual and monthly samples indicate that there are also other influential factors. Accordingly, differences in metal/metalloid concentrations between monthly samples cannot be overcome by adjusting the data to a common CI or a common length.

Seasonality in concentrations of covered chemicals

Figure 3 shows the monthly and annual wet weight-based data for Co, As, Hg and MeHg. Respective data for all other analyzed substances are given in Additional file 1: Figures S2–S4. At both North Sea sites, Co was highest in spring and summer followed by a clear decrease. Lowest levels were detected in winter. At the Baltic Sea site, higher Co levels were detected in winter samples. Arsenic was highest in spring and decreased thereafter at the North Sea site Koenigshafen, whereas no such seasonality was detected at the North Sea site Eckwarderhoerne and the Baltic Sea site. For Hg and MeHg no consistent patterns were observed.

Fig. 3
figure3figure3

Concentrations (ng g−1 wet weight ww) of cobalt, arsenic, total mercury and methylmercury in blue mussel (Mytilus edulis Complex) sampled at the North Sea sites Eckwarderhoerne and Koenigshafen and at the Baltic Sea site Darsser Ort. Shown are time trends for annual composite samples covering the years 2000–2017 (continuous line = significant linear or non-linear trend; dashed line = trend not significant; p = 0.05) as well as monthly concentrations in 2013, 2015 and 2017; for mercury the EQS is given as red line. Note the different scaling of the y-axis for total Hg and MeHg at Darsser Ort

For all other metals and metalloids more or less consistent seasonal patterns were observed which, however, differed between sites. At Koenigshafen, for instance, copper concentration was highest in spring and summer in 2015 and 2017, while in 2013 highest concentrations were detected in summer and fall (August–October). At Eckwarderhoerne, highest Cu levels were always observed in August (Additional file 1: Figures S2 and S3).

Based on these data, no consistent seasonality can be identified for any locations and all year. Seasonality differed between sampling sites and partly also between years (most likely because of differences in environmental conditions) which makes it difficult to pick one or two representative sampling times that would best reflect the annual mean.

According to published data, seasonal variations in metal burdens of mussel appear to be lower in marine regions than in estuarine environments, and maximum levels are typically detected in spring or winter (e.g., [13, 42]. Amiard et al. [12] monitored Pb, Cd, Cu and Zn in mussels from the Bay of Bourgneuf (France) on a monthly basis over more than 2 years and observed highest levels in winter and early spring. The authors attributed these seasonal differences to fluctuations in soft tissue weight related to the reproductive cycle. Similarly, Farrington et al. [15] reported considerably higher Pb, Cd, and Ni levels from October to March in mussels studied under the US Mussel Watch Program. In a study using transplanted mussels in Arcachon Bay (France), Devier et al. [14] demonstrated that As, Cd, chromium (Cr), Ni, Pb, selenium (Se), Zn all showed a similar seasonal pattern with highest concentrations in winter (December–March) and lowest in summer (June–October), whereas Cu remained more or less constant throughout the year. Regoli and Orlando [43] analyzed Cu, Fe, manganese (Mn), and Zn in the digestive gland of mussels (M. galloprovincialis) from a polluted and an unpolluted site in the Tyrrhenian Sea and found a pronounced seasonality with highest levels at the end of the spawning season in February/March and lowest in late summer at the beginning of another spawning period. Rainbow et al. [18] observed limited seasonal variation for Zn and Cu concentrations in M. trossulus of the Gulf of Gdansk (Baltic Sea).

It has to be kept in mind that some of the analyzed elements may be essential for bivalves, e.g., Cu, Zn, Co and Se, and may be subject to internal regulation [44,45,46].

For organic substances, seasonal patterns in mussel burdens seem to be different and less constant. Compounds that accumulate in lipid-rich tissues will likely be highest when body content of lipid is highest. For DDT, highest levels in oysters (Crassostrea gigas) were detected in summer when lipid-rich gametes are produced [22]. PCBs in blue mussels were detected mainly in gametes and mussel contamination decreased significantly after the spawning period [47,48,49]. Suarez et al. [23] observed a direct relationship between levels of PCBs, DDTs and HCHs in blue mussels (M. galloprovincialis) and their lipid content and reproductive stage. In contrast, Webster et al. [50] found no correlations between lipid contents of blue mussels and concentrations of PBDE, PAH and PCB. In the case of compounds like, e.g., pharmaceuticals, personal care products [24] or TBT, the observed seasonality in mussel contamination was obviously related to seasonal differences in emissions. Devier et al. [14] found high levels of TBT in mussels at harbor sites in summer when boat activities were highest. In contrast, Zanon et al. [26] and Tang et al. [25] report peak TBT concentrations in mussels also in winter at sites influenced by shipping maintenance activities in dry docks that are more frequent in winter.

Comparison between seasonal fluctuations and long-term trends

For all metals and metalloids, seasonal variations in body burdens observed in 2013, 2015 and 2017 were compared with long-term trends of these elements in annual composite samples over the last 17 years. The aim was to assess whether seasonality can mask long-term trends. Figure 3 shows the trends for the years 2000–2017 (TBT 2006–2017) based on the annual composite sample concentration data for Co, As, total Hg (THg) and MeHg as well as the seasonal fluctuations in the monthly samples for the years 2013, 2015 and 2017. Respective data for all other analyzed substances are given in Additional file 1: Figures S2–S4. Regarding the annual composite samples, Co concentration increased significantly since 2000 at both North Sea sites, whereas no such trend is detectable at the Baltic Sea site. In contrast, As increased at the North Sea site Koenigshafen and at the Baltic Sea site Darsser Ort but not at Eckwarderhoerne. For THg, a decreasing linear trend is observable at all three sites, while MeHg increased at Koenigshafen (but not at Eckwarderhoerne and Darsser Ort). Comparing the total Hg concentrations with the Environmental Quality Standard (EQS) of 20 ng g−1 ww [51] reveals that in recent years, the EQS is met at both North Sea sites. At the Baltic Sea site, Hg levels in mussels were generally lower and complied with the EQS during the entire study period.

In Fig. 4 the fraction of MeHg/THg is shown for the annual composite samples (years 2000–2017) from all sites and for the monthly samples of 2013, 2015 and 2017 from the North Sea sites. The data reveal that the MeHg/THg fraction differs between both North Sea sites. In annual composite samples from Eckwarderhoerne, the fraction between 2000 and 2017 is in the range of 20–30%. The same fraction is also found in the monthly samples from Eckwarderhoerne. By contrast, higher fractions around 30–50% were observed at the North Sea site Koenigshafen. At the Baltic Sea site, the MeHg/THg fraction in annual composite samples ranges between 20 and 45% during the study period. A clear seasonal variation of the fraction MeHg/THg for the North Sea sampling sites is not observable.

Fig. 4
figure4

Fraction of methylmercury and total mercury (MeHg/THg) in blue mussels (Mytilus edulis Complex) from the North Sea and Baltic Sea sampling sites of the German Environmental Specimen Bank. Shown are the fraction for annual composite samples covering the years 2000–2017, the monthly fractions for 2013, 2015 and 2017 (only North Sea sites) and the seasonal variation in MeHg/THg at the North Sea sites

Tables 1, 2, 3 summarize the monthly data of the years 2013, 2015 and 2017 and compare them to the range of the concentrations over a period of 17 years (for TBT, 11 years). The comparison reveals that the concentration ranges of the annual samples during in this period are in the same order of magnitude as the concentration ranges within 1 year (seasonal samples). The only exception is TBT which has continuously decreased over the last years so that the concentrations in 2013, 2015 and 2017 (covered by the monthly samples) were clearly lower than in the years before (which also contribute to the range of the annual composite samples). This was especially pronounced at Eckwarderhoerne. The data are consistent with previous findings relating the decrease of TBT following international bans [52].

Table 1 Comparison of seasonal and long-term variations in metal burdens (given as ng g−1 wet weight and dry weight) of blue mussels (Mytilus edulis) from the North Sea sampling site Eckwarderhoerne
Table 2 Comparison of seasonal and long-term variations in metal burdens (given as ng g−1 wet weight and dry weight) of blue mussels (Mytilus edulis) from the North Sea sampling site Koenigshafen
Table 3 Comparison of seasonal and long-term variations in metal burdens (given as ng g−1 wet weight and dry weight) of blue mussels (Mytilus edulis Complex) from the Baltic Sea sampling site Darsser Ort

The metal burdens of the seasonal and annual samples were compared to available Environmental Quality Standards (EQS) related to fish [51] and to threshold values (BAC or EC maximum food level) [53] given by OSPAR [54] and also applied by HELCOM [55]. The respective concentrations are shown in Additional file 1: Tables S6–S8, while Additional file 1: Tables S9–11 summarize the results. EQS and thresholds are available for Cd, Pb and Hg (EQS related to fish). Concentrations of Cd and Pb in mussels from both North Sea sites mostly exceed the respective threshold values (the only exceptions were Pb in samples from Koenigshafen in 2013 and 2015). In mussels from the Baltic Sea site Darsser Ort, Cd-levels exceeded the threshold in all samples, whereas the Pb-threshold was exceeded only in 2017. For mercury, the picture is vice versa. The majority of the mussel samples from all three sites meet the EQS of 20 ng g−1 wet weight. However, when compared with the EC maximum food levels which are used by OSPAR (i.e., 500 ng g−1) all samples meet the criteria. Since the EQS is derived to ensure environmental protection [56], it would be the more appropriate reference here, however, with the limitation that is derived for fish. There are no further EQS for heavy metals like cadmium referring to fish nor for mussel.

Conclusions

The present data demonstrate that seasonal fluctuations of metal-, metalloid-, and TBT-concentrations in blue mussels may be quite strong and vary between years and sampling locations. Moreover, for some metals seasonal fluctuation may be more pronounced than long-term trends. For trend monitoring it is therefore crucial to maintain fixed sampling times throughout the entire program. Monitoring program, such as the German ESB, which have analyzed and archived annual pool samples (each consisting of several monthly samples) over a longer period of time, are not recommended to reduce the annual sampling frequency as this may disrupt the already existing long time series.

Moreover, it is currently discussed that marine samples of the ESB may be used also in the context of Descriptor 9 of the Marine Strategy Framework Directive [57, 58]. This would require the best possible knowledge of mussel contamination for compliance assessment. Finally, ESB programs archive environmental samples for future analyses of yet unknown compounds or compounds for which sufficient sensitive analytical methods are still missing. Reducing sampling frequencies bears the risk of not recognizing (season-dependent) peak concentrations. It is therefore recommended to pool a fraction of the monthly samples to annual samples and use these for routine analysis (which reduces the costs for analysis) while also archiving the monthly mussel samples to allow for the retrospective analysis of monthly trends of pollutants and other stressor in future.

Availability of data

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request or can be downloaded from the homepage of the German Environment Specimen bank (www.umweltprobenbank.de/en).

Abbreviations

ESB:

Environmental Specimen Bank

TBT:

tributyltin

DBT:

dibutyltin

MBT:

monobutyltin

NIST:

National Institute of Standards and Technology

ICP-MS:

inductively coupled plasma-mass spectrometry

SOP:

Standard Operation Procedures

AAS:

atomic absorption spectrometry

DMA:

direct mercury analyzer

SID-GC/ICP-MS:

stable isotope dilution-gas chromatography coupled to inductively coupled plasma-mass spectrometry

TMAH:

tetramethylammoniumhydroxide

WW:

wet weight

Sn:

tin

Hg:

mercury

MeHg:

methylmercury

NaOAc/AcOH:

acetic buffer

GC:

gas chromatography

Cd:

cadmium

Cu:

copper

Cr:

chromium

As:

arsenic

Se:

selenium

Mn:

manganese

DDT:

dichlorodiphenyltrichloroethane

PCB:

polychlorinated biphenyl

HCH:

hexachlorocyclohexane

PAH:

polycyclic aromatic hydrocarbons

PBDE:

polybrominated diphenyl ethers

EQS:

Environmental Quality Standard

BAC:

Background Assessment Concentrations

References

  1. 1.

    EC (2010) Guidance document no. 25 on chemical monitoring of sediment and biota under the Water Framework Directive. Common implementation strategy for the Water Framework Directive (2000/60/EC). Technical Report—2010-041. ISBN 978-92-79-16224-4. Office for Official Publications of the European Communities, Luxembourg

  2. 2.

    OSPAR (2010) Intertidal Mytilus edulis beds on mixed and sandy sediments. Quality status report 2010—case reports for the OSPAR list of threatened and/or declining species and habitats. OSPAR

  3. 3.

    Beyer J et al (2017) Blue mussels (Mytilus edulis spp.) as sentinel organisms in coastal pollution monitoring: a review. Mar Environ Res 130:338–365

  4. 4.

    Davies IM, Vethaak AD (2012) Integrated marine environmental monitoring of chemicals and their effects. In: Anderson ED (ed) ICES cooperative research report. ICES, Copenhagen, p 289

  5. 5.

    OSPAR (2018) CEMP—guidelines for monitoring contaminants in biota. OSPAR Commission

  6. 6.

    HELCOM (2006) Manual for marine monitoring in the COMBINE programme of HELCOM part D programme for monitoring of contaminants and their effects

  7. 7.

    Darr A et al (2013) Population structure of long-lived macrozoobenthic species. In: HELCOM (ed) HELCOM core indicator report. HELCOM

  8. 8.

    Christensen JH et al (2002) Polybrominated diphenyl ethers (PBDEs) in marine fish and blue mussels from southern Greenland. Chemosphere 47(6):631–638

  9. 9.

    Riget F et al (2010) Temporal trends of legacy POPs in Arctic biota, an update. Sci Total Environ 408(15):2874–2884

  10. 10.

    Goldberg ED (1986) The Mussel Watch concept. Environ Monit Assess 7(1):91–103

  11. 11.

    Farrington JW et al (2016) Edward D. Goldberg’s proposal of “the Mussel Watch”: reflections after 40 years. Mar Pollut Bull 110(1):501–510

  12. 12.

    Amiard JC et al (1986) Contribution to the ecotoxicological study of cadmium, lead, copper and zinc in the mussel Mytilus edulis. 1: field study. Mar Biol 90:425–431

  13. 13.

    Cossa D (1989) A review of the use of Mytilus spp. as quantitative indicators of cadmium and mercury contamination in coastal waters. Oceanol Acta 12:417–432

  14. 14.

    Devier MH et al (2005) One-year monitoring survey of organic compounds (PAHs, PCBs, TBT), heavy metals and biomarkers in blue mussels from the Arcachon Bay, France. J Environ Monit 7(3):224–240

  15. 15.

    Farrington JW et al (1983) US “Mussel Watch” 1976–1978: an overview of the trace-metal, DDE, PCB, hydrocarbon and artificial radionuclide data. Environ Sci Technol 17(8):490–496

  16. 16.

    Oaten JFP et al (2017) Seasonal effects to metallothionein responses to metal exposure in a naturalised population of Ruditapes philippinarum in a semi-enclosed estuarine environment. Sci Total Environ 575:1279–1290

  17. 17.

    Perosevic A et al (2018) The impacts of seawater physicochemical parameters and sediment metal contents on trace metal concentrations in mussels—a chemometric approach. Environ Sci Pollut Res Int 25(28):28248–28263

  18. 18.

    Rainbow PS et al (2004) Geographical and seasonal variation of trace metal bioavailabilities in the Gulf of Gdansk, Poland using mussels (Mytilus edulis) and barnacles (Balanus improvisus). Mar Biol 144:271–286

  19. 19.

    Rajeshkumar S et al (2018) Studies on seasonal pollution of heavy metals in water, sediment, fish and oyster from the Meiliang Bay of Taihu Lake in China. Chemosphere 191:626–638

  20. 20.

    Fattorini D et al (2008) Seasonal, spatial and inter-annual variations of trace metals in mussels from the Adriatic sea: a regional gradient for arsenic and implications for monitoring the impact of off-shore activities. Chemosphere 72(10):1524–1533

  21. 21.

    Phillips DJH (1976) Common mussel Mytilus edulis as an indicator of pollution by zinc, cadmium, lead and copper. I. Effects of environmental variables on uptake of metals. Mar Biol 38:59–69

  22. 22.

    Butler PA (1973) Residues in fish, wildlife, and estuaries; organochlorine residues in estuarine mollusks, 1965–72—National Pesticide Monitoring Program. Pestic Monit J 6(4):238–362

  23. 23.

    Suarez P et al (2013) Organochlorine compounds in mussels cultured in the Ria of Vigo: accumulation and origin. Chemosphere 90(1):7–19

  24. 24.

    Granek EF et al (2016) Spatial and temporal variability of contaminants within estuarine sediments and native Olympia oysters: a contrast between a developed and an undeveloped estuary. Sci Total Environ 557–558:869–879

  25. 25.

    Tang CH, Hsu CH, Wang WH (2010) Butyltin accumulation in marine bivalves under field conditions in Taiwan. Mar Environ Res 70(2):125–132

  26. 26.

    Zanon F et al (2009) Time trend of butyl- and phenyl-tin contamination in organisms of the Lagoon of Venice (1999–2003). Environ Monit Assess 152(1–4):35–45

  27. 27.

    Ytreberg E et al (2016) XRF measurements of tin, copper and zin in antifouling paints coated on leisure boats. Environ Pollut 213:594–599

  28. 28.

    Andral B et al (2004) Monitoring chemical contamination levels in the Mediterranean based on the use of mussel caging. Mar Pollut Bull 49(9–10):704–712

  29. 29.

    Casas S et al (2008) Relation between metal concentration in water and metal content of marine mussels (Mytilus galloprovincialis): impact of physiology. Environ Toxicol Chem 27(7):1543–1552

  30. 30.

    Fisher H (1988) Mytilus edulis as a quantitative indicator of dissolved cadmium. Final study and synthesis. Mar Ecol Prog Ser 48:163–174

  31. 31.

    EC (2014) Common implementation strategy for the Water Framework Directive (2000/60/EC): guidance document no. 32 on biota monitoring (the implementation of EQSBiota) under the Water Framework Directive. European Commission

  32. 32.

    Paulus M, Klein R, Teubner D (2018) German Environmental Specimen Bank: guideline for sampling and sample treatment blue mussel (Mytilus edulis-Complex). Standard Operating Procedure (SOP). https://www.umweltprobenbank.de/en/documents/publications/26658

  33. 33.

    Rüdel H, Uhlig S, Weingärtner M (2009) German Environment Specimen Bank: guidelines for sampling and sample processing. Pulverisation and homogenisation of environmental samples by cryomilling. Standard Operating Procedure (SOP). https://www.umweltprobenbank.de/upb_static/fck/download/IME_SOP_preparation_Dez2008_V200.pdf

  34. 34.

    Rüdel H et al (2011) Richtlinie zur chemischen Analyse. Aufschluss von Umweltproben. In: Verfahrensrichtlinien für Probenahme, Transport, Lagerung und chemische Charakterisierung von Umwelt- und Humanproben. Fraunhofer IME, Schmallenberg/Umweltbundesamt, Dessau-Roßlau. https://www.umweltprobenbank.de/upb_static/fck/download/SOP_Aufschluss.pdf

  35. 35.

    Rüdel H, Kösters J, Schörmann J (2011) Richtlinie zur chemischen Analyse. Bestimmung von Elementgehalten in Umweltproben durch ICP-MS, V 2.1.0. In: Verfahrensrichtlinien für Probenahme, Transport, Lagerung und chemische Charakterisierung von Umwelt- und Humanproben. https://www.umweltprobenbank.de/upb_static/fck/download/SOP_ICP-MS_de.pdf

  36. 36.

    Nguetseng R et al (2015) Retrospective monitoring of mercury in fish from selected European freshwater and estuary sites. Chemosphere 134:427–434

  37. 37.

    Monperrus M et al (2004) Potential and limits of speciated isotope-dilution analysis for metrology and assessing environmental reactivity. Tr Anal Chem 23:267–272

  38. 38.

    Davis WC et al (2007) Certification of methylmercury content in two fresh-frozen reference materials: SRM 1947 Lake Michigan fish tissue and SRM 1974b organics in mussel tissue (Mytilus edulis). Anal Bioanal Chem 387(7):2335–2341

  39. 39.

    Point D et al (2007) Development and application of an ultratrace method for speciation of organotin compounds in cryogenically archived and homogenized biological materials. Anal Bioanal Chem 387(7):2343–2355

  40. 40.

    Paulus M et al (2015) Bioaccumulation and long-term monitoring in freshwater ecosystems—knowledge gained from 20 years of zebra mussel analysis by the German Environmental Specimen Bank. In: Armon RH, Hänninen O (eds) Environmental indicators. Vancouver, Fraser Institut

  41. 41.

    Fryer RJ, Nicholson MD (1999) Using smoothers for comprehensive assessments of contaminant time series in marine biota. ICES J Mar Sci 56:779–790

  42. 42.

    Gueguen M et al (2011) Shellfish and residual chemical contaminants: hazards, monitoring, and health risk assessment along French coasts. Rev Environ Contam Toxicol 213:55–111

  43. 43.

    Regoli F, Orlando E (1994) Seasonal variation of trace metal concentrations in the digestive gland of the Mediterranean mussel Mytilus galloprovincialis: comparison between a polluted and a non-polluted site. Arch Environ Contam Toxicol 27(1):36–43

  44. 44.

    Amiard JC et al (1987) Comparative study of the patterns of bioaccumulation of essential (Cu, Zn) and non-essential (Cd, Pb) trace metals in various estuarine and coastal organisms. J Exp Mar Biol Ecol 106(1):73–89

  45. 45.

    Phillips DJH, Rainbow PS (1988) Barnacles and mussels as biomonitors of trace elements: a comparative study. Mar Ecol Prog Ser 49:83–93

  46. 46.

    Simkiss K, Taylor M, Mason AZ (1982) Metal detoxification and bioaccumulation in molluscs. Mar Biol Lett 3(4/6):187–201

  47. 47.

    Hummel H et al (1990) Spatial and seasonal differences in the PCB content of the mussel Mytilus edulis. Sci Total Environ 92:155–163

  48. 48.

    Hummel H et al (1989) Relationship between PCB concentrations and reproduction in mussels Mytilus edulis. Mar Environ Res 28:489–543

  49. 49.

    Lee KM, Kruse H, Wassermann O (1996) Seasonal fluctuation of organochlorines in Mytilus edulis L. from the South West Baltic Sea. Chemosphere 32:1883–1895

  50. 50.

    Webster L et al (2009) An assessment of persistent organic pollutants (POPs) in wild and rope grown blue mussels (Mytilus edulis) from Scottish coastal waters. J Environ Monit 11(6):1169–1184

  51. 51.

    EC (2013) Directive 2013/39/EU of the European Parliament and of the Council of 12 August 2013 amending Directives 2000/60/EC and 2008/105/EC as regards priority substances in the field of water policy. Official Journal of the European Union, L226/1, 24.8.2013

  52. 52.

    Rudel H et al (2007) Retrospective monitoring of organotin compounds in freshwater fish from 1988 to 2003: results from the German environmental specimen bank. Chemosphere 66(10):1884–1894

  53. 53.

    Commission Regulation (EC) (2006) No 1881/2006 of 19 December 2006 setting maximum levels for certain contaminants in foodstuffs. Official Journal of the European Union, L364/5, 20.12.2006

  54. 54.

    OSPAR (2010) Agreement on CEMP assessment criteria for the QSR 2010. Agreement number: 2009-2. Publication number_2009/461. OSPAR Commission

  55. 55.

    HELCOM (2019) HELCOM indicators. Threshold and status evaluation. http://www.helcom.fi/baltic-sea-trends/indicators/metals/thresholds-and-status-evaluation

  56. 56.

    Guidance Document No: 27 (2008) Technical guidance for deriving environmental quality standards common implementation strategy for the Water Framework Directive (2000/60/EC). 2011: technical report—2011-055

  57. 57.

    EC (2008) Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive). Official Journal of the European Union, L164/19, 25.6.2008

  58. 58.

    Fliedner A et al (2018) Assessment of seafood contamination under the marine strategy framework directive: contributions of the German environmental specimen bank. Environ Sci Pollut Res Int 25(27):26939–26956

Download references

Acknowledgements

The authors thank all personnel of the University of Trier involved in the samplings and of the Fraunhofer IME involved in the preparation and the measurement of the samples.

Funding

This work was funded by the German Environment Agency within the scope of the Environment Specimen Bank program.

Author information

BK was responsible for the metal analyses and statistical evaluation of all data; GR analyzed organotin compounds; BK, AF, JK and HR performed the data analysis and were involved in manuscript writing. MP was responsible for the mussel sampling and involved in manuscript writing. UP was involved in comparison of data with the regulations and manuscript writing. All authors read and approved the final manuscript.

Correspondence to Burkhard Knopf.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Additional file 1: Table S1. ICP-MS parameters for metal and metalloid measurements. Table S2. GC parameters, GC temperature program and ICP-MS parameters for organotin measurements. Table S3. Correlation (p ≤ 0.05, non-directional) between the shell length of mussels and concentrations of analyses elements/compounds. Table S4. Correlation (p ≤ 0.05, non-directional) between the condition index of mussels and concentrations of elements/compounds. NS: North Sea, BS: Baltic Sea. Table S5. Correlation (p ≤ 0.05, non-directional) between the condition index of mussels and wet weight-based concentrations of elements/compounds—comparison between annual and monthly samples. NS: North Sea, BS: Baltic Sea. Table S6. Cd-concentrations (ng g−1 dry weight dw and wet weight ww) of monthly samples and annual composite samples of blue mussels (Mytilus edulis Complex) from North Sea and Baltic Sea sites. For comparison: BAC and EC maximum food level used by HELCOM and OSPAR (wet weight based data without respiratory water). Table S7. Pb-concentrations (ng g−1 dry weight dw and wet weight ww) of monthly samples and annual composite samples of blue mussels (Mytilus edulis Complex) from North Sea and Baltic Sea sites. For comparison: BAC and EC maximum food level used by HELCOM and OSPAR (wet weight based data without respiratory water). Table S8. Hg concentrations (ng g−1 wet weight) of monthly samples and annual composite samples of blue mussels (Mytilus edulis Complex) from North Sea and Baltic Sea site. For comparison: BAC and EC maximum food level used by HELCOM and OSPAR and the Water Framework Directive (Directive 2013/39/EU) (wet weight based data without respiratory water). Table S9. Comparison of Cd-thresholds used by HELCOM and OSPAR with Cd-concentrations in seasonal and annual composite samples of blue mussels (Mytilus edulis Complex) from North Sea and Baltic Sea sites (wet weight based data without respiratory water). Table S10. Comparison of Pb-threshold values used by HELCOM and OSPAR with Pb-concentrations in monthly samples and annual composite samples of blue mussels (Mytilus edulis Complex) from sampling sites North Sea and Baltic Sea sites (wet weight based data without respiratory water). Table S11. Comparison of Hg-thresholds used by HELCOM, OSPAR and the WFD with THg-concentrations in monthly and annual composite samples of blue mussels (Mytilus edulis Complex) from North Sea and Baltic Sea sites (wet weight based data without respiratory water). Figure S1. Biometrical parameters of blue mussels (Mytilus edulis Complex) from the sampling sites of the German environmental specimen bank in the North Sea (Eckwarderhoerne, Koenigshafen) and the Baltic Sea (Darsser Ort). Shown are data of monthly samples and of annual composite samples of the respective year (dark columns). Figure S2. Long-term trends and seasonal variations in concentrations of metals in blue mussel (Mytilus edulis Complex) sampled at the North Sea site Eckwarderhoerne. Upper row: long-term trends based on annual composite samples (continuous line = significant linear or non-linear trend; dashed line = trend not significant; p = 0.05); lower row: seasonal variation based on bi-monthly samples from 2013, 2015, and 2017. Figure S3: Long-term trends and seasonal variations in concentrations of metals in blue mussel (Mytilus edulis Complex) sampled at the North Sea site Koenigshafen. Upper row: long-term trends based on annual composite samples (continuous line = significant linear or non-linear trend; dashed line = trend not significant; p = 0.05); lower row: seasonal variation based on bi-monthly samples from 2013, 2015, and 2017. Figure S4. Long-term trends and seasonal variations in concentrations of metals in blue mussel (Mytilus edulis Complex) sampled at the Baltic Sea site Darsser Ort. Upper row: long-term trends based on annual composite samples (continuous line = significant linear or non-linear trend; dashed line = trend not significant; p = 0.05); lower row: seasonal variation based on 6-month samples from 2013, 2015, and 2017.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Knopf, B., Fliedner, A., Radermacher, G. et al. 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. Environ Sci Eur 32, 7 (2020). https://doi.org/10.1186/s12302-020-0289-7

Download citation

Keywords

  • Heavy metals
  • Metalloid
  • Seasonal variability
  • Monitoring
  • Mussels