Field Testing a Metal Bioaccumulation Model for Zebra Mussels
Bibliographic record
Abstract
A kinetic model of trace element bioaccumulation in zebra mussels, employing experimentally determined trace element influx and efflux rates following food and water exposures, was field-tested in the Hudson and Niagara Rivers and Lakes Erie and Ontario. Ultraclean measurements of water column trace element concentrations in these waters and on suspended particles were used to predict metal concentrations in zebra mussels that were measured independently by the NOAA Mussel Watch program. Field concentrations of Ag, Cd, Cr, and Hg ranged from sub-picomolar (Ag) to low nanomolar (Cr) and displayed partition coefficients between particulate and aqueous phases of 1−20 × 10 5 L kg - 1 . Despite variation in bioaccumulation factors (BAF) between locations by up to 6× (for Ag), our model predicted mean body burdens of Ag, Cr, Hg, and Se that differed from measured tissue concentrations at the same sites by only 30% on average. Cd predictions matched measured values at the two lake sites but exceeded measurements at the three river sites by 2.6-fold. Furthermore, the model predicted that, under all environmental conditions likely to prevail in natural waters, Ag, Cd, and Hg are predominantly accumulated from ingested particles, that Cr is accumulated mostly from the dissolved phase, and that the relative uptake pathway for Se varies with environmental conditions. The highest BAF was for Cd (15−64 × 10 4 ) and the lowest BAFs were for Cr and Se (1.2−2.5 × 10 4 and 0.5−2.8 × 10 4, respectively), with Ag and Hg being intermediate (2.0−12 × 10 4 and 1.4−25 × 10 4, respectively). The good agreement of the model with field measurements suggests, for these elements, that (a) accumulation of these elements in zebra mussels is in fact proportional to influx from food and water (that is, the organism is not actively regulating internal concentrations), and (b) we can account for the processes governing metal bioaccumulation in these animals. We conclude that for these elements the zebra mussel will be effective as a bioindicator of ambient metals in freshwater systems.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".