Antecedent moisture conditions control mercury and dissolved organic carbon concentration dynamics in a boreal headwater catchment
Bibliographic record
Abstract
Abstract The fate and transport of mercury (Hg) deposited on forested upland soils depends on the biogeochemical and hydrological processes occurring in the soil landscape. In this study, total Hg (THg) and dissolved organic carbon (DOC) concentrations were measured in streamwater from a 7.75 ha upland subcatchment of the METAALICUS watershed in northwestern Ontario, Canada. THg and DOC concentration‐discharge relationships were examined at the seasonal‐scale and event‐scale to assess the role of antecedent moisture conditions on the mobilization of these solutes to receiving waters. At the seasonal‐scale, subcatchment discharge poorly explained THg and DOC concentration dynamics; however, the inclusion of antecedent water storage and precipitation metrics in a multiple regression model improved the prediction of THg and DOC concentrations significantly. At the event‐scale, a comparison of THg and DOC concentrations for two small summer storms with similar total discharge showed that the storm following the wet snowmelt period had a significantly lower total flux of THg and DOC than the storm following warm and dry conditions in late summer due to a distinct shift in the concentration‐discharge relationship. Measurements of soil water and groundwater THg and DOC concentrations, as well as a three‐component mixing analysis, suggest that there was an accumulation of potentially‐mobile DOC‐bound THg in the well‐humified organic soil layer in the catchment during the warm and dry summer period and that as the catchment became wetter in the autumn, there was an increase in soil water THg and DOC concentrations and these solutes were subsequently flushed during the autumn storm.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".