Mercury in Nelson's Sparrow Subspecies at Breeding Sites
Bibliographic record
Abstract
BACKGROUND: Mercury is a persistent, biomagnifying contaminant that can cause negative effects on ecosystems. Marshes are often areas of relatively high mercury methylation and bioaccumulation. Nelson's Sparrows (Ammodramus nelsoni) use marsh habitats year-round and have been documented to exhibit tissue mercury concentrations that exceed negative effects thresholds. We sought to further characterize the potential risk of Nelson's Sparrows to mercury exposure by sampling individuals from sites within the range of each of its subspecies. METHODOLOGY/PRINCIPAL FINDINGS: From 2009 to 2011, we captured adult Nelson's Sparrows at sites within the breeding range of each subspecies (A. n. nelsoni: Grand Forks and Upham, North Dakota; A. n. alterus: Moosonee, Ontario; and A. n. subvirgatus: Grand Manan Island, New Brunswick) and sampled breast feathers, the first primary feather (P1), and blood for total mercury analysis. Mean blood mercury in nelsoni individuals captured near Grand Forks ranged from 0.84 ± 0.37 to 1.65 ± 1.02 SD ppm among years, between 2.0 and 4.9 times as high as concentrations at the other sites (P<0.01). Breast feather mercury did not vary among sites within a given sampling year (site means ranged from 0.98 ± 0.69 to 2.71 ± 2.93 ppm). Mean P1 mercury in alterus (2.96 ± 1.84 ppm fw) was significantly lower than in any other sampled population (5.25 ± 2.24-6.77 ± 3.51 ppm; P ≤ 0.03). CONCLUSIONS/SIGNIFICANCE: Our study further characterized mercury in Nelson's Sparrows near Grand Forks; we documented localized and potentially harmful mercury concentrations, indicating that this area may represent a biological mercury hotspot. This finding warrants further research to determine if wildlife populations of conservation or recreational interest in this area may be experiencing negative effects due to mercury exposure. We present preliminary conclusions about the risk of each sampled population to mercury exposure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".