Precipitation input and antecedent soil moisture effects on mercury mobility in soil—laboratory experiments with an enriched stable isotope tracer
Bibliographic record
Abstract
Abstract Terrestrial soils are net mercury (Hg) sinks, but leaching of Hg from upland environments constitutes an important source to downstream wetlands and water bodies. Broadly, hydrology is instrumental in facilitating Hg transport within, and export from watersheds but the relative influences of specific hydrological factors such as antecedent soil moisture and precipitation in controlling the transport of Hg through upland soils are not well understood. The purpose of this research was to elucidate the relative controls of these hydrological factors using a full factorial laboratory experiment involving the application of an enriched stable Hg isotope tracer to intact soil cores. Antecedent soil moisture and precipitation input depth were statistically significant, mutually exclusive controls on tracer Hg mobility. Neither factor however had a strongly significant influence on the mobility of ambient Hg. Tracer Hg mobility was enhanced with larger precipitation events as well as from initially drier soils and appeared to move via simple piston flow. The majority (>99.5%) of added tracer Hg was sorbed to soil organic matter in the surface 3 cm, regardless of the hydrological treatment combinations. Overall, these results suggest that tracer and ambient Hg are differentially controlled by hydrological conditions. Changes in hydrology may have little impact on ambient Hg mobilization in sandy loam soils. If tracer Hg is broadly representative of contemporary soil Hg stocks, extreme precipitation events among otherwise drier conditions could enhance the export of contemporary Hg from upland systems. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".