Polybrominated Diphenyl Ethers (PBDEs): Turning the Corner in Great Lakes Trout 1980–2009
Bibliographic record
Abstract
Lake trout and walleye composites were collected between 2004 and 2009 as part of the Great Lakes Fish Monitoring and Surveillance Program (GLFMSP) and analyzed for polybrominated diphenyl ethers (PBDEs). Yearly mean total PBDE concentrations (sum of congeners BDE-47, BDE-99, BDE-100, BDE-153, BDE-154) ranged from 44-192, 28-113, 50-107, 37-111, and 11-22 ng/g wet wt. for Lakes Michigan, Huron, Ontario, and Superior lake trout, and Lake Erie walleye, respectively. A 1980-2009 temporal record of PBDE concentrations in the Great Lakes' top predator fish (lake trout and walleye) was assembled by integrating previous GLFMSP data (1980-2003) with current results (2004-2009). Temporal profiles show obvious breakpoints between periods of PBDE accumulation and decline in trout for Lakes Huron, Michigan and Ontario with a significant (p < 0.0001 and r = 0.55, 0.72, and 0.51, respectively) decrease in concentration after 2000-2001. A similar transition was observed in Lake Superior for the nearshore site accompanied by a less significant decreasing trend (p = 0.016, r = 0.33), suggesting concentrations are declining very slowly or have leveled off. In contrast, Lake Erie walleye concentrations began leveling off in the late 1990s and no statistically significant trend (increasing or decreasing) has been observed in recent years. A decrease in the BDE-47/BDE-153 ratio was also recently observed, suggesting a transition to more highly brominated PBDEs is occurring in Great Lakes trout. This study provides region-wide evidence that PBDE concentrations are generally declining in Great Lakes trout, although there are clear exceptions to this trend. Results from this study reflect the positive impact of the 2004 PentaBDE ban on macro-scale aquatic freshwater ecosystems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".