Effects of trophic status and wetland morphology, hydroperiod, and water chemistry on mercury concentrations in fish
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We sampled fish and selected water chemistry variables (dissolved organic carbon, sulfate, and pH) in nine southeastern depression wetlands to determine relationships among wetland morphology (surface area and maximum depth), hydrology, water chemistry, and bioaccumulation of mercury (Hg) in fishes. We concentrated on three fish species representing the range of trophic levels occupied by fish in southeastern depression wetlands. Whole-body Hg concentrations were lowest in lake chubsucker (Erimyzon sucetta), a benthic detritivore, and highest in redfin pickerel (Esox americanus americanus), a top carnivore. However, variation in Hg concentrations among wetlands was greater than variation among species. Regression analyses indicated that maximum depth and hydroperiod accounted for significant portions of variation among wetlands in standardized lake chubsucker and redfin pickerel Hg concentrations. Maximum depth and dissolved organic carbon had a negative effect on standardized Hg concentrations in mud sunfish (Acantharchus pomotis). Path analysis confirmed the results of regression analyses, with maximum depth and hydroperiod having relatively large direct negative effects on Hg concentrations. Our results suggest that leaching of Hg from sediments during the drying and reflooding cycle and binding of Hg species by dissolved organic carbon in the water column are primary factors controlling the bioavailability of Hg in southeastern depression wetlands.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it