J. Great Lakes Res. 29(2):332–354 Internat. Assoc. Great Lakes Res., 2003 Assessing Trends in Organochlorine Concentrations in Lake Winnipeg Fish Following the 1997 Red River Flood
Bibliographic record
Abstract
ABSTRACT. As we move toward the virtual elimination of persistent organic pollutants (POPs) in the environment our understanding of how short-term variability affects long-term trends of POPs in natural populations will become increasingly more important. In this study we report short-term trends in organochlorine (OC) levels in fish from Lake Winnipeg in the months and years following the 1997 100-year flood of the Red River ecosystem. Our goal was to understand the effects of an episodic event on OC levels in benthic and pelagic invertebrates and in fish. Despite elevated loading of OCs into the south basin of Lake Winnipeg during the flood there were no differences in OC levels of surface sediments or emergent mayflies. After adjusting for differences in lipid content and length among sample times, we did find significant increases in total DDT (∑DDT) and total polychlorinated biphenyl (∑PCB) post-flood (March 1999) in top predators including walleye and burbot. Significant increases were also observed in OC concentrations of zooplankton and yellow perch (> 2 fold in ∑PCB, ∑DDT, total chlordane (∑CHL), total chlorobenzenes (∑CBZ)) and walleye (1.4 fold ∑PCB) over a 2-month period in the summer follow-ing the flood. Analysis of specific congener patterns over time suggest that the major changes in fish OC levels pre- and post-flood did not appear to be linked to transport of new compounds into the Lake during the flood, but to species shifts within the plankton community. Our results indicate that short-term varia-tion (~2 months) in OC distributions within biota may be equal to or greater than those resulting from episodic events such as spring floods. INDEX WORDS: Bioaccumulation, PCB, DDT, floods, food webs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.014 |
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".