Agricultural pesticides and ectoparasites: potential combined effects on the physiology of a declining aerial insectivore
Bibliographic record
Abstract
Abstract Agricultural pesticides usage has been increasing globally. These compounds have been developed to disrupt pest species physiology, but because their specificity is limited, they can also have adverse effects on non-target organisms. Recent studies have shown that the damaging toxicological effects of pesticides can be amplified in stressful environments. However, few studies have documented these effects in natural settings where organisms are simultaneously exposed to pesticides and to other environmental stressors such as parasites. In this study, we assessed both pesticide and ectoparasite effects on the physiology of a free-ranging bird. We measured physiological markers including haematocrit, bacteria-killing ability (BKA) and leucocyte counts, as well as exposure to haematophagous Protocalliphora larvae, in tree swallow nestlings (Tachycineta bicolor), a declining aerial insectivore, in southern Québec, Canada, for over 3 years. We found that combined exposure to pesticides and Protocalliphora larvae was negatively related to haematocrit, suggesting possible synergistic effects. However, we found no such relationships with BKA and leucocyte counts, highlighting the complexity of physiological responses to multiple stressors in natural settings. Populations of several aerial insectivores are declining, and although sublethal pesticide effects on physiology are suspected, our results suggest that exposure to other factors, such as parasitism, should also be considered to fully assess these effects, especially because pesticides are increasingly present in the environment.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".