Biomagnification of DDT through the Benthic and Pelagic Food Webs of Lake Malawi, East Africa: Importance of Trophic Level and Carbon Source
Bibliographic record
Abstract
Lake Malawi, an East African Rift Valley lake, is internationally renowned for having the highest diversity of fish species in the world, and these cichlids are highly specialized in their dietary habits. In this lake, tissue stable carbon (delta13C) and nitrogen (delta15N) isotopes can be used over several trophic levels to distinguish those consumers relying upon carbon fixed by either benthic or pelagic primary producers. As such, it was possible to contrast the biomagnification of persistent organochlorines through the benthic and pelagic food webs. In 1996 and 1997, food-web organisms were collected from Lake Malawi and analyzed for organochlorines, delta13C and delta15N to determine the factors that affectthe biomagnification of contaminants in a tropical lake. The pesticide DDT was the most predominant pollutant in the biota from Lake Malawi and was found at the highest concentrations in the largest and fattiest fish species. As observed in temperate systems, log-transformed sigmaDDT concentrations in food-web organisms were significantly predicted by delta15N or log lipid (r2 = 0.32 and 0.40, respectively). In addition, the slope of the regression of log sigmaDDT versus delta15N was significantly higher in the pelagic than the benthic food web. These results indicate that pelagic organisms are at greater risk of accumulating these pollutants than biota relying upon benthic primary production.
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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 | 0.000 | 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 | 0.000 | 0.010 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".