Temporal trends of mercury levels in fish (dab, Limanda limanda) and sediment from the German Bight (North Sea) in the period 1995–2020
Bibliographic record
Abstract
As a toxic and harmful global pollutant, mercury (Hg) enters the marine environment through natural sources, and human activities. It bioaccumulates through the food chain and therefore, Hg is of great importance for environmental monitoring. This study aims to answer the question if Hg contamination in fish and sediment from the German Bight follows temporal trends. Therefore, 496 individual female dab (Limanda limanda) were analyzed. The Hg concentrations in the muscle of dab from the German Bight showed significant increase in function of time with an annual percental change of 1.4%, leading to a 41% increase in Hg contamination level within 25 years of monitoring. At the same time, Hg concentrations in sediment—analyzed in 86 samples—significantly decreased in the nearby North Sea environment. This surprising contradiction is shown in the present study and possible causes are discussed. It could be clearly shown that contamination in sediment and biota can follow completely different time courses and therefore, different environmental matrices should be considered in future monitoring studies. Age of the fish turned out to be a biological factor of particular importance for temporal trend analysis. Methode Mercury in fish The determination of Hg in fish from 1995 to 2009 followed the protocol described by Harms (1981, 1998). Briefly, wet samples were subjected to a pressure digestion by nitric acid in PTFE tubes heated up to 135 °C for 2 h. This was partly supported by a microwave system, “MLS-Ethos-plus” (MLS Mikrowellen Labor-Systeme GmbH, Leutkirch, Germany). Mercury was determined by cold vapor atomic absorption spectrometry using a flow injection mercury system Model 420 (Perkin Elmer, Rodgau, Germany) with background compensation and Hg lamp. A clean bench was used to avoid contamination during sample processing. The limit of detection (LD) was calculated according to DIN 32,645 (DIN, 1994) and was always below 1.2 μg Hg/kg wet weight (ww). The method used from 2010 to determine Hg in fish is in detail described in Kammann et al. (2021). Briefly, samples were freeze-dried using a lyophilizer (LD 1–2,Christ, Osterode, Germany) and subsequently homogenized using an agate mortar or an ultra Turrax tube drive dispenser (IKA, Staufen, Germany) to obtain a dry and homogenous sample powder. Total Hg was determined by atomic absorption spectrometry using a Direct Mercury Analyzer (DMA-80, MLS, Leutkirch, Germany). A total of 20–30 mg of each sample were weighted into the boat containers of the DMA-80. Direct analysis for total Hg content was performed using a 10-level calibration with standards in 0.5 M nitric acid. The LD and the limit of quantification (LQ) were calculated from a standard curve according to DIN 32,645 (DIN, 1994) with a confidence level of 99%. Considering the sample preparation, a LD of 0.080 μg/kg ww and a LQ of 0.230 μg/kg ww were determined for Hg. No values below these limits were found in any sample under investigation. Preparation steps were carried out under clean benches all the time. Clean lab conditions of ISO class 7 were available since 2018. Nitric acid (69%, ultrapure quality) and certified standard solutions of Hg were purchased from Carl Roth, Karlsruhe, Germany, in 0.5 M nitric acid. Ultrapure water was obtained from a Purelab Flex 3 device (Elga Veolia; High Wycombe, UK). The accuracy of the Hg measurement in fish was determined by analysis of Certified Reference Materials (e.g., DORM-4) obtained from the National Research Council (NRC) in Canada which was taken through the same analytical procedure as the samples. All samples were measured in triplicates. External quality assurance was done by participation in laboratory proficiency tests conducted by QUASIMEME (www.wepal.nl) designed for marine environment analytics from 1997 to 2021. Results of 55 QUASIMEME intercalibrations are presented in Table S1 with a mean z-score of 0.09 and only 7% of unsatisfying results (z-score > = │2.5│).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".