Assessing pesticides exposure effects on the reproductive performance of a declining aerial insectivore
Bibliographic record
Abstract
In the context of increasing global environmental changes, it has become progressively important to understand the effects of human activity on wildlife populations. Declines in several avian populations have been observed since the 1970s, especially with respect to many farmland and grassland birds, which also include some aerial insectivores. Changes in farming practices referred to as agricultural intensification coincide with these major avian declines. Among those practices, increased pesticide use is hypothesized to be a key driver of avian population declines as it can lead to both toxicological and trophic effects. While numerous laboratory studies report that birds experience acute and chronic effects upon consuming pesticide treated food, little is known about the effects of the exposure to multiple pesticides on wildlife in natural settings. We monitored the breeding activities of Tree Swallows (Tachycineta bicolor) on 40 farms distributed over a gradient of agricultural intensification in southern Québec, Canada, to evaluate the presence of pesticides in their diet and quantify the exposure effects of those compounds on their reproductive performance between 2013 and 2018. We first assessed the presence of 54 active agents (or derivatives) found in pesticides in 2,081 food boluses (insects) delivered to nestlings by parents and documented their spatial distribution within our study area. Second, we assessed the effect of pesticide exposure through food (number of active agents detected and number of contaminated boluses on a given farm for a given year, while controlling for sampling effort) on clutch size as well as hatching and fledging successes and nestling's mass upon fledging. Pesticides were ubiquitous in our study system and nearly half (46%) of food boluses were contaminated by at least one active agent. Yet we found no relationship between our proxies of food contamination by pesticides and Tree Swallow reproductive performance. More studies are needed to better understand the putative role of pesticides in the decline of farmland birds and aerial insectivores as potential sublethal effects of pesticides can carry over to later life stages and impact fitness.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".