Temporal trends of mercury in Arctic biota: 10 more years of progress in Arctic monitoring

Temporal trend analysis of (total) mercury (THg) concentrations in Arctic biota were assessed as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) Mercury Assessment. A mixed model including an evaluation of non-linear trends was applied to 110 time series of THg concentrations from Arctic and Subarctic biota. Temporal trends were calculated for full time series (6–46 years) and evaluated with a particular focus on recent trends over the last 20 years. Three policy-relevant questions were addressed: (1) What time series for THg concentrations in Arctic biota are currently available? (2) Are THg concentrations changing over time in biota from the Arctic? (3) Are there spatial patterns in THg trends in biota from the Arctic? Few geographical patterns of recent trends in THg concentrations were observed; however, those in marine mammals tended to be increasing at more easterly longitudes, and those of seabirds tended to be increasing in the Northeast Atlantic; these should be interpreted with caution as geographic coverage remains variable. Trends of THg in freshwater fish were equally increasing and decreasing or non-significant while those in marine fish and mussels were non-significant or increasing. The statistical power to detect trends was greatly improved compared to the 2011 AMAP Mercury Assessment; 70% of the time series could detect a 5% annual change at the 5% significance level with power ≥ 80%, while in 2011 only 19% met these criteria. Extending existing time series, and availability of new, powerful time series contributed to these improvements, highlighting the need for annual monitoring, particularly given the spatial and temporal information needed to support initiatives such as the Minamata Convention on Mercury. Collecting the same species/tissues across different locations is recommended. Extended time series from Alaska and new data from Russia are also needed to better establish circumarctic patterns of temporal trends.