Field and Laboratory Evidence That Chlorpyrifos Exposure Reduced the Population Density of a Freshwater Snail by Increasing Juvenile Mortality
Bibliographic record
Abstract
Pesticides have been frequently detected in global freshwater ecosystems, but attempts to document changes in population dynamics of organisms upon exposure to pesticides, establish a causal relationship between exposure and population effects, and identify the key toxic events within individuals under natural field conditions remain rare. Here, we used a field survey, a reciprocal cross-transplant experiment, and a laboratory toxicity experiment to build a compelling case that exposure to the insecticide chlorpyrifos was responsible for differences in snail ( Bellamya aeruginosa ) densities in eastern (ELL) and western basins of Liangzi Lake in China. Our field survey and reciprocal cross-transplant experiment revealed significant differences in snail densities, juvenile percentage, survival, and relative telomere length (RTL) in the two basins. The insecticide chlorpyrifos detected in snail tissues was negatively correlated with snail densities, the percentage of juvenile snails, and RTL and had an extremely high risk quotient in ELL. In the laboratory experiment, tissue concentrations of chlorpyrifos detected in ELL were associated with reduced RTL and increased juvenile mortality in B. aeruginosa . These results support the hypothesis that chlorpyrifos exposure in ELL reduced the density of snails by reducing juvenile survival and, consequently, recruitment to the adult population.
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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".