Heavy metals, selenium, and Pacific Dunlin: patterns of accumulation, exposure from prey and toxicity risks
Bibliographic record
Abstract
My research objectives for the thesis were: 1) Investigate factors that contribute to heavy metal and selenium dietary exposure and accumulation in Dunlin (Calidris alpina). 2) Examine the potential for adverse effects to Dunlin from such elements. To pursue these objectives I examined elements in feather and kidney tissues and analyzed ingested items in gizzard contents. Habitat preference (terrestrial vs estuarine), trophic level, age, sex, bill length, and size were investigated as factors potentially influencing element accumulation. Toxicity risks associated with accumulated element burdens and dietary exposure were assessed with comparisons to levels of demonstrated adverse effects for avian species. I report concentrations of cadmium, copper, and zinc in kidneys as well as copper, mercury, selenium, lead, and zinc in feathers. Cadmium concentrations in kidneys increased logarithmically with age. Cadmium accumulated to a greater degree in Dunlin that foraged in estuarine habitat as compared to more terrestrial feeders. Cadmium, copper and zinc in kidneys did not occur at concentrations known to incur deleterious health or reproductive effects. Copper, lead, and zinc concentrations in feathers were within documented ranges for sandpipers and/or below levels associated with adverse effects. Mercury in feathers of some Dunlin nearly reached concentrations associated with risks of adverse effects. Selenium in feathers of most individuals exceeded the threshold above which toxicity risks are present. Daily exposure to cadmium, copper, and zinc was determined for six diet types. Diets from agricultural fields were lower in all metals than terrestrial diets from birds collected at Vancouver International Airport (YVR). Diets containing mostly sediment exposed Dunlin to low amounts of metals compared to other diet types. Cadmium exposure was greatest the diet type containing mostly mud snails (Batillaria attramentaria), and copper and zinc exposures were greatest in YVR diets. Exposure was concerning as eight of eighteen assessments predicted probable toxic effects. Exposure risk is mitigated by co-abundance of metals and Dunlin’s tendency to feed in both estuarine and terrestrial habitats. Potential issues with applying daily exposure models to estuarine feeding sandpipers with relatively high metabolisms as compared to other avian species are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".