Investigation of Uptake and Retention of Atmospheric Hg(II) by Boreal Forest Plants Using Stable Hg Isotopes
Bibliographic record
Abstract
Although there is now a general consensus among mercury (Hg) biogeochemists that increased atmospheric inputs of inorganic Hg(II) to lakes and watersheds can result in increased methylmercury (MeHg) concentrations in fish, researchers still lack kinetic data describing the movement of Hg from the atmosphere, through watershed and lake ecosystems, and into fish. The use of isotopically enriched Hg species in environmental studies now allows experimentally applied new Hg to be distinguished from ambient Hg naturally present in the system. Four different enriched stable Hg(II) isotope "spikes" were applied sequentially over four years to the ground vegetation of a microcatchment at the Experimental Lakes Area (ELA) in the remote boreal forest of Canada to examine retention of Hg(II) following deposition. Areal masses of the spikes and ambient THg (all forms of Hg in a sample) were monitored for eight years, and the pattern of spike retention was used to estimate retention of newly deposited ambient Hg within the ground vegetation pool. Fifty to eighty percent of applied spike Hg was initially retained by ground vegetation. The areal mass of spike Hg declined exponentially over time and was best described by a first-order process with constants(k) ranging between 9.7 x 10(-40 day(-1) and 11.6 x 10(-4) day(-1). Average halflife (t1/2) of spike Hg within the ground vegetation pool (+/-S.D.) was 704 +/- 52 days. This retention of new atmospheric Hg(II) by vegetation delays movement of new Hg(II) into soil, runoff, and finally into adjacent lakes. Ground-applied Hg(II) spikes were not detected in tree foliage and litterfall, indicating that stomatal and/or root uptake of previously deposited Hg (i.e., "recycled" from ground vegetation or soil Hg pools) were likely not large sources of foliar Hg under these experimental conditions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| 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 teacher head, 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".