Review of the Influence of Climate Change on the Hydrologic Cycling and Gaseous Fluxes of Mercury in Boreal Peatlands: Implications for Restoration
Bibliographic record
Abstract
Mercury (Hg) is a pollutant that bioaccumulates in the food web, leading to health issues in humans and other fauna. Although anthropogenic Hg deposition has decreased over the past 20 years, our watersheds continue to be sources of Hg to downstream communities. Wetlands, especially peatlands in the Boreal Region of the globe, play a vital role in the formation of bioaccumulative methylmercury (MeHg). Few studies have assessed how increases in temperatures such as those that have already occurred and those predicted will influence the hydrologic transport of Hg to downstream communities or the net fluxes of gaseous Hg. The results indicate that peatland pore water concentrations of MeHg are increasing with ecosystem warming, and to some degree with elevated carbon dioxide (eCO2) in the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment at the Marcell Experimental Forest (MEF) in northern Minnesota, USA. Similar to SPRUCE, in the Biological Response to A Changing Environment (BRACE) experiment in Canada, mesocosm pore water MeHg concentrations increased with soil warming. However, long-term peatland watershed streamflow fluxes of MeHg at the MEF indicate that the competing effects of climate warming and decreased atmospheric deposition have led to overall decreases in watershed MeHg transport. Mesocosm studies in the PEATCOSM experiment in Upper Michigan, USA, indicate that simulated fluctuating water tables led to higher concentrations of MeHg in peatland pore water that is available for downstream transport when water tables rise and the next runoff event occurs. Results from a winter peatland soil freeze/thaw simulation from large mesocosm cores from Jennie’s Bog at the MEF indicate higher total Hg (THg) upon soil thawing but lower MeHg, likely a result of cold temperatures limiting methylation during thawing. Although there are lower MeHg concentrations after thawing, more THg is available for methylation once soils warm. Results from PEATCOSM and the literature also suggest that plant community changes that result in higher densities of sedges also lead to elevated MeHg in pore water. From a climate warming perspective, it appears that two complementary mechanisms, both related to decomposition, are at play that lead to increased pore water MeHg concentrations with warming. First, warming increases decomposition rates, leading to a higher availability of many ions, including Hg (and sulfur) species. Higher decomposition rates also lead to increases in soluble carbon which complexes with Hg species and assists in downstream hydrologic transport. However, if streamflow is decreasing with climate change as a result of landscape-level changes in evapotranspiration as suggested at MEF, the combination of less direct watershed Hg deposition and lower streamflow results in decreases in the watershed transport of MeHg. Given changes already occurring in extreme events and the rewetting and restoration of hydrology during peatland restoration, it is likely that methylation and pore water MeHg concentrations will increase. However, the landscape-level hydrologic cycle will be key to understanding the connection to downstream aquatic communities. Finally, gaseous Hg fluxes increase with warming and lead to decreases in peatland pools of Hg that may influence future availability for downstream transport.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".